Clinical and Biologic Correlates of ADORA2A Transcriptomic Expression in Cancer

ADORA2A (adenosine A2a receptor) and ADORA2B propagate immunoregulatory signals, including restricting both innate and adaptive immunity, though recent data also suggest a tumor suppressor effect in certain settings. We evaluated the RNA expression from 514 tumors in a clinical-grade laboratory; 489 patients with advanced/metastatic disease had clinical outcome correlates. Transcript expression was standardized to internal housekeeping genes and ranked (0-100 scale) relative to 735 specimens from 35 different cancer types. Transcript abundance rank values were defined as "low/moderate" (0-74) or "high" (75-100) percentile RNA expression ranks. Overall, 20.8% of tumors had high ADORA2A (≥75 percentile RNA rank). The greatest proportion of high ADORA2A expressors was found in neuroendocrine and breast cancers and sarcomas, whereas the lowest was found in colorectal and ovarian cancers, albeit with patient-to-patient variability. In multivariable logistic regression analysis, there was a significant positive correlation between high ADORA2A RNA expression and a high expression of the immune checkpoint-related molecules PD-1 (p = 0.015), VISTA (p ≤ 0.001), CD38 (p = 0.031), and CD39 (p ≤ 0.001). In 217 immunotherapy-treated patients, high ADORA2A did not correlate significantly with progression-free (p = 0.51) or overall survival (OS) (p = 0.09) from the initiation of the checkpoint blockade. However, high versus not-high ADORA2A transcript expression correlated with longer OS from the time of advanced/metastatic disease (N = 489 patients; (HR 0.69 (95% CI 0.51-0.95) (p = 0.02)). Therefore, high ADORA2A transcript levels may be a favorable prognostic factor, unrelated to immunotherapy. Importantly, ascertaining co-expression patterns of ADORA2A with PD-1 and VISTA in individual tumors as a basis for the precision co-targeting of ADORA2A and these other checkpoint-related molecules warrants investigation in clinical trials.

High indoleamine 2,3-dioxygenase transcript levels predict better outcome after front-line cancer immunotherapy

Indoleamine 2,3-dioxygenase 1 (IDO1), which catabolizes tryptophan, is a potential target to unlock the immunosuppressive tumor microenvironment. Correlations between IDO1 and immune checkpoint inhibitor (ICI) efficacy remain unclear. Herein, we investigated IDO1 transcript expression across cancers and clinical outcome correlations. High IDO1 transcripts were more frequent in uterine (54.2%) and ovarian cancer (37.2%) but varied between and within malignancies. High IDO1 RNA expression was associated with high expression of PD-L1 (immune checkpoint ligand), CXCL10 (an effector T cell recruitment chemokine), and STAT1 (a component of the JAK-STAT pathway) (all multivariable p < 0.05). PIK3CA and CTCF alterations were more frequent in the high IDO1 group. High IDO1 expression was an independent predictor of progression-free survival (adjusted HR = 0.44, 95% CI 0.20-0.99, p = 0.049) and overall survival (adjusted HR = 0.31, 95% CI 0.11-0.87, p = 0.026) after front-line ICIs. IDO1 expression warrants further exploration as a predictive biomarker for immunotherapy. Moreover, co-expressed immunoregulatory molecules merit exploration for co-targeting.

Transcriptomic analysis of GITR and GITR ligand reveals cancer immune heterogeneity with implications for GITR targeting

Glucocorticoid-induced tumor necrosis factor related protein (GITR) is a transmembrane protein expressed mostly on CD25+CD4+ regulatory T-cells (Tregs) and upregulated on all T-cells upon activation. It is a T-cell co-stimulatory receptor and has demonstrated promising anti-tumor activity in pre-clinical studies. To date, however, the efficacy of GITR agonism has been discouraging in clinical trials. This study explores GITR and GITR ligand (GITR-L) ribonucleic acid (RNA) expression in solid tumors in an attempt to delineate causes for variable responses to GITR agonists. RNA expression levels of 514 patients with a variety of cancer types were normalized to internal housekeeping gene profiles and ranked as percentiles. 99/514 patients (19.3%) had high GITR expression (defined as ≥ 75th percentile). Breast and lung cancer had the highest proportion of patients with high GITR expression (39% and 35%, respectively). The expression of concomitant high GITR and low-moderate GITR-L expression (defined as <75th percentile) was present in 31% and 30% of patients with breast and lung cancer respectively. High GITR expression also showed a significant independent association with high RNA expression of other immune modulator proteins, namely, PD-L1 immunohistochemistry (IHC) ≥1 (odds ratio (OR) 2.15, P=0.008), CTLA4 (OR=2.17, P=0.05) and OX40 high RNA expression (OR=2.64, P=0.001). Overall, these results suggest that breast and lung cancer have a high proportion of patients with a GITR and GITR-L RNA expression profile that merits further investigation in GITR agonism studies. The association of high GITR expression with high CTLA4 and OX40 RNA expression, as well as positive PD-L1 IHC, provides a rationale for a combination approach targeting these specific immune modulator proteins in patients whose tumors show such co-expression.

Viewing the immune checkpoint VISTA: landscape and outcomes across cancers

BACKGROUND

Optimizing immune checkpoint inhibitor (ICI) therapy may require identification of co-targetable checkpoint pathways via immune profiling. Herein, we analyzed the transcriptomic expression and clinical correlates of V-domain immunoglobulin suppressor of T-cell activation (VISTA), a promising targetable checkpoint.

PATIENTS AND METHODS

RNA sequencing was carried out on 514 tissues reflecting diverse advanced/metastatic cancers. Expression of eight immune checkpoint markers [lymphocyte-activation gene 3 (LAG-3), tumor necrosis factor receptor superfamily 14 (TNFRSF14), programmed cell death protein 1 (PD-1), programmed death-ligand 1 (PD-L1), programmed death-ligand 2 (PD-L2), B- and T-lymphocyte attenuator (BTLA), T-cell immunoglobulin and mucin domain-containing protein 3 (TIM-3), cytotoxic T-lymphocyte antigen 4 (CTLA-4)], in addition to VISTA, was analyzed, along with clinical outcomes.

RESULTS

High VISTA RNA expression was observed in 32% of tumors (66/514) and was the most common highly expressed checkpoint among the nine assessed. High VISTA expression was independently correlated with high BTLA, TIM-3, and TNFRSF14, and with a diagnosis of pancreatic, small intestine, and stomach cancer. VISTA transcript levels did not correlate with overall survival (OS) from metastatic/advanced disease in the pan-cancer cohort or with immunotherapy outcome (progression-free survival and OS from the start of ICI) in 217 ICI-treated patients. However, in ICI-treated pancreatic cancer patients (n = 16), median OS was significantly shorter (from immunotherapy initiation) for the high- versus not-high-VISTA groups (0.28 versus 1.21 years) (P = 0.047); in contrast, VISTA levels were not correlated with OS in 36 pancreatic cancer patients who did not receive ICI.

CONCLUSION

High VISTA expression correlates with high BTLA, TIM-3, and TNFRSF14 checkpoint-related molecules and with poorer post-immunotherapy survival in pancreatic cancer, consistent with prior literature indicating that VISTA is prominently expressed on CD68+ macrophages in pancreatic cancers and requiring validation in larger prospective studies. Immunomic analysis may be important for individualized precision immunotherapy.

OX40/OX40 ligand and its role in precision immune oncology

Immune checkpoint inhibitors have changed the treatment landscape for various malignancies; however, their benefit is limited to a subset of patients. The immune machinery includes both mediators of suppression/immune evasion, such as PD-1, PD-L1, CTLA-4, and LAG-3, all of which can be inhibited by specific antibodies, and immune-stimulatory molecules, such as T-cell co-stimulatory receptors that belong to the tumor necrosis factor receptor superfamily (TNFRSF), including OX40 receptor (CD134; TNFRSF4), 4-1BB (CD137; TNFRSF9), and glucocorticoid-induced TNFR-related (GITR) protein (CD357; TNFRSF18). In particular, OX40 and its binding ligand OX40L (CD134L; TNFSF4; CD252) are critical for immunoregulation. When OX40 on activated T cells binds OX40L on antigen-presenting cells, T-cell activation and immune stimulation are initiated via enhanced T-cell survival, proliferation and cytotoxicity, memory T-cell formation, and abrogation of regulatory T cell (Treg) immunosuppressive functions. OX40 agonists are in clinical trials both as monotherapy and in combination with other immunotherapy agents, in particular specific checkpoint inhibitors, for cancer treatment. To date, however, only a minority of patients respond. Transcriptomic profiling reveals that OX40 and OX40L expression vary between and within tumor types, and that only ~ 17% of cancer patients have high OX40 and low OX40L, one of the expression patterns that might be theoretically amenable to OX40 agonist enhancement. Taken together, the data suggest that the OX40/OX40L machinery is a critical part of the immune stimulatory system and that understanding endogenous expression patterns of these molecules and co-existing checkpoints merits further investigation in the context of a precision immunotherapy strategy for cancer therapy.

The Impact of Prior Single-Gene Testing on Comprehensive Genomic Profiling Results for Patients with Non-Small Cell Lung Cancer

INTRODUCTION

Tissue-based broad molecular profiling of guideline-recommended biomarkers is advised for the therapeutic management of patients with non-small cell lung cancer (NSCLC). However, practice variation can affect whether all indicated biomarkers are tested. We aimed to evaluate the impact of common single-gene testing (SGT) on subsequent comprehensive genomic profiling (CGP) test outcomes and results in NSCLC.

METHODS

Oncologists who ordered SGT for guideline-recommended biomarkers in NSCLC patients were prospectively contacted (May-December 2022) and offered CGP (DNA and RNA sequencing), either following receipt of negative SGT findings, or instead of SGT for each patient. We describe SGT patterns and compare CGP completion rates, turnaround time, and recommended biomarker detection for NSCLC patients with and without prior negative SGT results.

RESULTS

Oncologists in > 80 community practices ordered CGP for 561 NSCLC patients; 135 patients (27%) first had negative results from 30 different SGT combinations; 84% included ALK, EGFR and PD-L1, while only 3% of orders included all available SGTs for guideline-recommended genes. Among patients with negative SGT results, CGP was attempted using the same tissue specimen 90% of the time. There were also significantly more CGP order cancellations due to tissue insufficiency (17% vs. 7%), DNA sequencing failures (13% vs. 8%), and turnaround time > 14 days (62% vs. 29%) than among patients who only had CGP. Forty-six percent of patients with negative prior SGT had positive CGP results for recommended biomarkers, including targetable genomic variants in genes beyond ALK and EGFR, such as ERBB2, KRAS (non-G12C), MET (exon 14 skipping), NTRK2/3, and RET .

CONCLUSION

For patients with NSCLC, initial use of SGT increases subsequent CGP test cancellations, turnaround time, and the likelihood of incomplete molecular profiling for guideline-recommended biomarkers due to tissue insufficiency.

Cancer testis antigen burden (CTAB): a novel biomarker of tumor-associated antigens in lung cancer

BACKGROUND

Cancer-testis antigens (CTAs) are tumor antigens that are normally expressed in the testes but are aberrantly expressed in several cancers. CTA overexpression drives the metastasis and progression of lung cancer, and is associated with poor prognosis. To improve lung cancer diagnosis, prognostic prediction, and drug discovery, robust CTA identification and quantitation is needed. In this study, we examined and quantified the co-expression of CTAs in lung cancer to derive cancer testis antigen burden (CTAB), a novel biomarker of immunotherapy response.

METHODS

Formalin fixed paraffin embedded (FFPE) tumor samples in discovery cohort (n = 5250) and immunotherapy and combination therapy treated non-small cell lung cancer (NSCLC) retrospective (n = 250) cohorts were tested by comprehensive genomic and immune profiling (CGIP), including tumor mutational burden (TMB) and the mRNA expression of 17 CTAs. PD-L1 expression was evaluated by IHC. CTA expression was summed to derive the CTAB score. The median CTAB score for the discovery cohort of 170 was applied to the retrospective cohort as cutoff for CTAB "high" and "low". Biomarker and gene expression correlation was measured by Spearman correlation. Kaplan-Meier survival analyses were used to detect overall survival (OS) differences, and objective response rate (ORR) based on RECIST criteria was compared using Fisher's exact test.

RESULTS

The CTAs were highly co-expressed (p < 0.05) in the discovery cohort. There was no correlation between CTAB and PD-L1 expression (R = 0.011, p = 0.45) but some correlation with TMB (R = 0.11, p = 9.2 × 10-14). Kaplan-Meier survival analysis of the immunotherapy-treated NSCLC cohort revealed better OS for the pembrolizumab monotherapy treated patients with high CTAB (p = 0.027). The combination group demonstrated improved OS compared to pembrolizumab monotherapy group (p = 0.04). The pembrolizumab monotherapy patients with high CTAB had a greater ORR than the combination therapy group (p = 0.02).

CONCLUSIONS

CTA co-expression can be reliably measured using CGIP in solid tumors. As a biomarker, CTAB appears to be independent from PD-L1 expression, suggesting that CTAB represents aspects of tumor immunogenicity not measured by current standard of care testing. Improved OS and ORR for high CTAB NSCLC patients treated with pembrolizumab monotherapy suggests a unique underlying aspect of immune response to these tumor antigens that needs further investigation.

LAG-3 transcriptomic expression correlates linearly with other checkpoints, but not with clinical outcomes

Immune checkpoint inhibitors have revolutionized the treatment landscape for patients with cancer. Multi-omics, including next-generation DNA and RNA sequencing, have enabled the identification of exploitable targets and the evaluation of immune mediator expression. There is one FDA-approved LAG-3 inhibitor and multiple in clinical trials for numerous cancers. We analyzed LAG-3 transcriptomic expression among 514 patients with diverse cancers, including 489 patients with clinical annotation for their advanced malignancies. Transcriptomic LAG-3 expression was highly variable between histologies/cancer types and within the same histology/cancer type. LAG-3 RNA levels correlated linearly, albeit weakly, with high RNA levels of other checkpoints, including PD-L1 (Pearson's R2 = 0.21 (P < 0.001)), PD-1 (R2 = 0.24 (P < 0.001)) and CTLA-4 (R2 = 0.19 (P < 0.001)); when examined for Spearman correlation, significance did not change. LAG-3 expression (dichotomized at ≥ 75th (high) versus < 75th (moderate/low) RNA percentile level) was not a prognostic factor for overall survival (OS) in 272 immunotherapy-naïve patients with advanced/metastatic disease (Kaplan Meier analysis; P = 0.54). High LAG-3 levels correlated with longer OS after anti-PD-1/PD-L1-based checkpoint blockade (univariate (P = 0.003), but not multivariate analysis (hazard ratio, 95% confidence interval = 0.80 (0.46-1.40) (P = 0.44))); correlation with longer progression-free survival showed a weak univariate trend (P = 0.13). Taken together, these results suggest that high LAG-3 levels in and of themselves do not predict resistance to anti-PD-1/PD-L1 checkpoint blockade. Even so, since LAG-3 is often co-expressed with PD-1, PD-L1 and/or CTLA-4, selecting patients for combinations of checkpoint blockade based on immunomic co-expression patterns is a strategy that merits exploration.

High CTLA-4 transcriptomic expression correlates with high expression of other checkpoints and with immunotherapy outcome

Background

CTLA-4 impedes the immune system's antitumor response. There are two Food and Drug Administration-approved anti-CTLA-4 agents - ipilimumab and tremelimumab - both used together with anti-PD-1/PD-L1 agents.

Objective

To assess the prognostic implications and immunologic correlates of high CTLA-4 in tumors of patients on immunotherapy and those on non-immunotherapy treatments.

Design/methods

We evaluated RNA expression levels in a clinical-grade laboratory and clinical correlates of CTLA-4 and other immune checkpoints in 514 tumors, including 489 patients with advanced/metastatic cancers and full outcome annotation. A reference population (735 tumors; 35 histologies) was used to normalize and rank transcript abundance (0-100 percentile) to internal housekeeping gene profiles.

Results

The most common tumor types were colorectal (140/514, 27%), pancreatic (55/514, 11%), breast (49/514, 10%), and ovarian cancers (43/514, 8%). Overall, 87 of 514 tumors (16.9%) had high CTLA-4 transcript expression (⩾75th percentile rank). Cancers with the largest proportion of high CTLA-4 transcripts were cervical cancer (80% of patients), small intestine cancer (33.3%), and melanoma (33.3%). High CTLA-4 RNA independently/significantly correlated with high PD-1, PD- L2, and LAG3 RNA levels (and with high PD-L1 in univariate analysis). High CTLA-4 RNA expression was not correlated with survival from the time of metastatic disease [N = 272 patients who never received immune checkpoint inhibitors (ICIs)]. However, in 217 patients treated with ICIs (mostly anti-PD-1/anti-PD- L1), progression-free survival (PFS) and overall survival (OS) were significantly longer among patients with high versus non-high CTLA-4 expression [hazard ratio, 95% confidence interval: 0.6 (0.4-0.9) p = 0.008; and 0.5 (0.3-0.8) p = 0.002, respectively]; results were unchanged when 18 patients who received anti-CTLA-4 were omitted. Patients whose tumors had high CTLA-4 and high PD-L1 did best; those with high PD-L1 but non-high CTLA-4 and/or other expression patterns had poorer outcomes for PFS (p = 0.004) and OS (p = 0.009) after immunotherapy.

Conclusion

High CTLA-4, especially when combined with high PD-L1 transcript expression, was a significant positive predictive biomarker for better outcomes (PFS and OS) in patients on immunotherapy.

Pan-cancer analysis of TIM-3 transcriptomic expression reveals high levels in pancreatic cancer and interpatient heterogeneity

BACKGROUND

T-cell immunoglobulin and mucin domain-containing protein 3 (TIM-3), an immune checkpoint receptor, dampens immune function. TIM-3 antagonists have entered the clinic.

METHODS

We analyzed TIM-3 transcriptomic expression in 514 diverse cancers. Transcript abundance was normalized to internal housekeeping genes and ranked (0-100 percentile) to a reference population (735 tumors; 35 histologies [high≥75 percentile rank]). Ninety tumors (17.5%) demonstrated high TIM-3 expression.

RESULTS

TIM-3 expression varied between and within tumor types. However, high TIM-3 expression was more common in pancreatic cancer (20/55 tumors, 36.4%; odds ratio, 95% confidence interval (pancreatic vs. other tumors) = 3.176 (1.733-5.818; p < 0.001, multivariate]). High TIM-3 also significantly and independently correlated with high PD-L1 (p = 0.014) and high CTLA-4 (p < 0.001) transcriptomic expression (multivariate).

CONCLUSIONS

These observations indicate that TIM-3 RNA expression is heterogeneous, but more common in pancreatic cancer and in tumors exploiting PD-L1 and CTLA-4 checkpoints. Clinical trials with patient selection for matched immune-targeted combinations may be warranted.

Cancer-Immunity Marker RNA Expression Levels across Gynecologic Cancers: Implications for Immunotherapy

Our objective was to characterize cancer-immunity marker expression in gynecologic cancers and compare immune landscapes between gynecologic tumor subtypes and with nongynecologic solid tumors. RNA expression levels of 51 cancer-immunity markers were analyzed in patients with gynecologic cancers versus nongynecologic cancers, and normalized to a reference population of 735 control cancers, ranked from 0 to 100, and categorized as low (0-24), moderate (25-74), or high (75-100) percentile rank. Of the 72 patients studied, 43 (60%) had ovarian, 24 (33%) uterine, and 5 (7%) cervical cancer. No two immune profiles were identical according to expression rank (0-100) or rank level (low, moderate, or high). Patients with cervical cancer had significantly higher expression level ranks of immune activating, proinflammatory, tumor-infiltrating lymphocyte markers, and checkpoints than patients with uterine or ovarian cancer (P < 0.001 for all comparisons). However, there were no significant differences in immune marker expression between uterine and ovarian cancers. Tumors with PD-L1 tumor proportional score (TPS) ≥1% versus 0% had significantly higher expression levels of proinflammatory markers (58 vs. 49%, P = 0.0004). Compared to patients with nongynecologic cancers, more patients with gynecologic cancers express high levels of IDO-1 (44 vs. 13%, P < 0.001), LAG3 (35 vs. 21%, P = 0.008), and IL10 (31 vs. 15%, P = 0.002.) Patients with gynecologic cancers have complex and heterogeneous immune landscapes that are distinct from patient to patient and from other solid tumors. High levels of IDO1 and LAG3 suggest that clinical trials with IDO1 inhibitors or LAG3 inhibitors, respectively, may be warranted in gynecologic cancers.

PD-L1 Expression by RNA-Sequencing in Non-Small Cell Lung Cancer: Concordance with Immunohistochemistry and Associations with Pembrolizumab Treatment Outcomes

Programmed cell death ligand (PD-L1) expression by immunohistochemistry (IHC) lacks sensitivity for pembrolizumab immunotherapy selection in non-small cell lung cancer (NSCLC), particularly for tumors with low expression. We retrospectively evaluated transcriptomic PD-L1 by mRNA next-generation sequencing (RNA-seq). In an unselected NSCLC patient cohort (n = 3168) tested during standard care (2017-2021), PD-L1 IHC and RNA-seq demonstrated moderate concordance, with 80% agreement overall. Most discordant cases were either low or negative for PD-L1 expression by IHC but high by RNA-seq. RNA-seq accurately discriminated PD-L1 IHC high from low tumors by receiver operator curve (ROC) analysis but could not distinguish PD-L1 IHC low from negative tumors. In a separate pembrolizumab monotherapy cohort (n = 102), NSCLC tumors classified as PD-L1 high versus not high by RNA-seq had significantly improved response, progression-free survival, and overall survival as an individual measure and in combination with IHC high or low status. PD-L1 IHC status (high or low) trended toward but had no significant associations with improved outcomes. Conventional PD-L1 IHC testing has inherent limitations, making it an imperfect reference standard for evaluating novel testing technologies. RNA-seq offers an objective PD-L1 measure that could represent a complementary method to IHC to improve NSCLC patient selection for immunotherapy.

T-cell priming transcriptomic markers: implications of immunome heterogeneity for precision immunotherapy

Immune checkpoint blockade is effective for only a subset of cancers. Targeting T-cell priming markers (TPMs) may enhance activity, but proper application of these agents in the clinic is challenging due to immune complexity and heterogeneity. We interrogated transcriptomics of 15 TPMs (CD137, CD27, CD28, CD80, CD86, CD40, CD40LG, GITR, ICOS, ICOSLG, OX40, OX40LG, GZMB, IFNG, and TBX21) in a pan-cancer cohort (N = 514 patients, 30 types of cancer). TPM expression was analyzed for correlation with histological type, microsatellite instability high (MSI-H), tumor mutational burden (TMB), and programmed death-ligand 1 (PD-L1) expression. Among 514 patients, the most common histological types were colorectal (27%), pancreatic (11%), and breast cancer (10%). No statistically significant association between histological type and TPM expression was seen. In contrast, expression of GZMB (granzyme B, a serine protease stored in activated T and NK cells that induces cancer cell apoptosis) and IFNG (activates cytotoxic T cells) were significantly higher in tumors with MSI-H, TMB ≥ 10 mutations/mb and PD-L1 ≥ 1%. PD-L1 ≥ 1% was also associated with significantly higher CD137, GITR, and ICOS expression. Patients' tumors were classified into "Hot", "Mixed", or "Cold" clusters based on TPM expression using hierarchical clustering. The cold cluster showed a significantly lower proportion of tumors with PD-L1 ≥ 1%. Overall, 502 patients (98%) had individually distinct patterns of TPM expression. Diverse expression patterns of TPMs independent of histological type but correlating with other immunotherapy biomarkers (PD-L1 ≥ 1%, MSI-H and TMB ≥ 10 mutations/mb) were observed. Individualized selection of patients based on TPM immunomic profiles may potentially help with immunotherapy optimization.

Challenges and prospects of CSF1R targeting for advanced malignancies

CSF1R expression modulates tumor-associated macrophages, making CSF1R blockade an appealing immune-modulating therapeutic target. We evaluated the correlation between CSF1R tumor RNA expression and outcome (pan-cancer setting). RNA expression was ranked as a percentile (0-100) using a standardized internal reference population (735 tumors; 35 histologies). Among 514 patients, there was no difference in survival from biopsy between high and low CSF1R expressors (< 50 percentile versus ≥ 50 percentile rank). There was also no significant difference in median progression-free or overall survival (from treatment) based on CSF1R expression in 21 patients who received CSF1R inhibitors (all p values ≥ 0.08). Concurrent upregulation of ≥ 2 additional immune checkpoint markers (e.g. PD-L1, BTLA, CTLA4, LAG3, TIM3) was observed in all tumor samples with CSF1R expression ≥ 50th percentile. Pending further large prospective studies, patients with high tumor CSF1R expression may need treatment that co-targets the specific immune checkpoint pathways activated in order to impact outcome.

RNA Sequencing Identifies Novel NRG1 Fusions in Solid Tumors that Lack Co-Occurring Oncogenic Drivers

NRG1 gene fusions are rare, therapeutically relevant, oncogenic drivers that occur across solid tumor types. To understand the landscape of NRG1 gene fusions, 4397 solid tumor formalin-fixed, paraffin-embedded samples consecutively tested by comprehensive genomic and immune profiling during standard care were analyzed. Nineteen NRG1 fusions were found in 17 unique patients, across multiple tumor types, including non-small-cell lung (n = 7), breast (n = 2), colorectal (n = 3), esophageal (n = 2), ovarian (n = 1), pancreatic (n = 1), and unknown primary (n = 1) carcinomas, with a cumulative incidence of 0.38%. Fusions were identified with breakpoints across four NRG1 introns spanning 1.4 megabases, with a mixture of known (n = 8) and previously unreported (n = 11) fusion partners. Co-occurring driver alterations in tumors with NRG1 fusions were uncommon, except colorectal carcinoma, where concurrent alterations in APC, BRAF, and ERBB2 were present in a subset of cases. The overall lack of co-occurring drivers highlights the importance of identifying NRG1 gene fusions, as these patients are unlikely to harbor other targetable alterations. In addition, RNA sequencing is important to identify NRG1 gene fusions given the variety of fusion partners and large genomic areas where breakpoints can occur.

Mechanisms of immune modulation in the tumor microenvironment and implications for targeted therapy

The efficacy of cancer therapies is limited to a great extent by immunosuppressive mechanisms within the tumor microenvironment (TME). Numerous immune escape mechanisms have been identified. These include not only processes associated with tumor, immune or stromal cells, but also humoral, metabolic, genetic and epigenetic factors within the TME. The identification of immune escape mechanisms has enabled the development of small molecules, nanomedicines, immune checkpoint inhibitors, adoptive cell and epigenetic therapies that can reprogram the TME and shift the host immune response towards promoting an antitumor effect. These approaches have translated into series of breakthroughs in cancer therapies, some of which have already been implemented in clinical practice. In the present article the authors provide an overview of some of the most important mechanisms of immunosuppression within the TME and the implications for targeted therapies against different cancers.

LAG-3 transcriptomic expression patterns across malignancies: Implications for precision immunotherapeutics

BACKGROUND

Lymphocyte activation gene 3 (LAG-3) or CD223 is a transmembrane protein that serves as an immune checkpoint which attenuates T-cell activation. Many clinical trials of LAG-3 inhibitors have had modest effects, but recent data indicate that the LAG-3 antibody relatlimab, together with nivolumab (anti-PD-1), provided greater benefit than nivolumab alone in patients with melanoma.

METHODS

In this study, the RNA expression levels of 397 genes were assessed in 514 diverse cancers at a clinical-grade laboratory (OmniSeq: https://www.omniseq.com/). Transcript abundance was normalized to internal housekeeping gene profiles and ranked (0-100 percentile) using a reference population (735 tumors; 35 histologies).

RESULTS

A total of 116 of 514 tumors (22.6%) had high LAG-3 transcript expression (≥75 percentile rank). Cancers with the greatest proportion of high LAG-3 transcripts were neuroendocrine (47% of patients) and uterine (42%); colorectal had among the lowest proportion of high LAG-3 expression (15% of patients) (all p < 0.05 multivariate); 50% of melanomas were high LAG-3 expressors. There was significant independent association between high LAG-3 expression and high expression of other checkpoints, including programmed death-ligand 1 (PD-L1), PD-1, and CTLA-4, as well as high tumor mutational burden (TMB) ≥10 mutations/megabase, a marker for immunotherapy response (all p < 0.05 multivariate). However, within all tumor types, there was inter-patient variability in LAG-3 expression level.

CONCLUSIONS

Prospective studies are therefore needed to determine if high levels of the LAG-3 checkpoint are responsible for resistance to anti-PD-1/PD-L1 or anti-CTLA-4 antibodies. Furthermore, a precision/personalized immunotherapy approach may require interrogating individual tumor immunograms to match patients to the right combination of immunotherapeutic agents for their malignancy.

Abstract P5-02-54: Application of low-pass whole genome sequencing for the detection of Homologous Recombination Deficiency in breast cancer

Background: Homologous recombination deficiency (HRD), broadly defined as a loss of the cellular mechanism underlying homologous recombination, is often observed in breast cancer. HRD causes distinctive perturbations to tumor genomic architecture that allow for its molecular identification, while also rendering HRD+ cancers vulnerable to specific chemotherapeutic interventions. This makes the molecular identification of HRD a promising avenue in precision medicine of breast cancer. Specific features of HRD include the presence of large-scale transitions (LST), telomeric allelic imbalance (TAI) and Loss of Heterozygosity (LOH). Each are readily detectable via targeted next generation sequencing (tNGS) or via array-based genotyping. However, genome-wide approaches for HRD detection using cost-effective methods, such as low-pass sequencing (LP-WGS), remain relatively under-explored. Here, we investigated whether HRD signals can be successfully re-capitulated using LP-WGS technology and benchmarked our results against the current field standard (both tNGS and array genotyping). Methods: LP-WGS and tNGS was performed on 96 samples across a range of tumor types (including N=17 breast cancer samples). LP-WGS libraries were prepared using Nextera (Illumina) using 0.4ng DNA input, and sequenced to 0.5-1x coverage. tNGS libraries were prepared using TSO500 (Illumina) using 40-80ng input, and sequenced to &gt;150x unique read coverage. Regions of CNV were estimated using CNVKit v0.9.6, and regions of LOH were estimated using a novel ancestry-aware method. Small variant detection was performed using the TSO500 v2.2.0.12 analysis pipeline. SNP array analysis of 12 tumor samples using Oncoscan (ThermoFisher) was also performed. CNV and LOH estimates derived from LP-WGS, TSO500 and SNP array data were calculated using Jaccard similarity, treating the SNP array data as the “ground truth”. Results: We benchmarked HRD signals derived from LP-WGS compared to the array-based calls and observed near perfect sensitivity for CNV gains across samples (Jaccard index=1.0), as well as for CNV losses between LP-WGS and SNP array (Jaccard index=1.0). We additionally noted that LPS-WGS calls captured both CNV loss and gains that were not detectable via the SNP array. For TAI, LP-WGS re-capitulated 7/10 unique signals also identified via array. We also observed high concordance between regions of the genome called LOH between both platforms (median Jaccard index=0.70, IQR=0.254), but noted an attenuation of sensitivity in samples where estimated tumor heterogeneity was high. We also evaluated LP-WGS CNV calls against the TSO500 assay and noted high sensitivity (96%; 94%) and specificity (89%; 91%) for both CNV gains and losses, respectively. Conclusions: Workflows incorporating LP-WGS can support the detection of HRD genome-wide, paving the way for a more affordable assay that may help to inform clinical decision making in the future treatment of breast cancer.

Citation Format: Gillian Belbin, Jie An, Chase Mazur, Joseph Pickrell, Jeremy Li, Daniel Metzger, Shuang Gao, Erik Van Roey, Robert Seager, Sarabjot Pabla, Durga Prasad Dash, Jeffrey M. Conroy. Application of low-pass whole genome sequencing for the detection of Homologous Recombination Deficiency in breast cancer [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P5-02-54.

Cancer immunity marker RNA expression levels across gynecologic cancers: Implications for immunotherapy

Background: Our objective was to characterize cancer immunity marker expression in gynecologic cancers and compare immune landscapes between gynecologic tumor subtypes and with non-gynecologic solid tumors. Methods: RNA expression levels of 51 cancer-immunity markers were analyzed in patients with gynecologic cancers vs. non-gynecologic cancers, and normalized to a reference population of 735 control cancers, ranked from 0-100, and categorized as low (0-24), moderate (25-74), or high (75-100) percentile rank. Results: Of the 72 patients studied, 43 (60%) had ovarian, 24 (33%) uterine, and 5 (7%) cervical cancer. No two immune profiles were identical according to expression rank (0-100) or rank level (low, moderate, or high). Patients with cervical cancer had significantly higher expression level ranks of immune activating, pro-inflammatory, tumor infiltrating lymphocyte markers and checkpoints than patients with uterine or ovarian cancer (p<0.001 for all comparisons). However, there were no significant differences in immune marker expression between uterine and ovarian cancers. Tumors with PD-L1 TPS =>1% versus 0% had significantly higher expression levels of pro-inflammatory markers (58 vs. 49%, p=0.0004). Compared to patients with non-gynecologic cancers, more patients with gynecologic cancers express high levels of IDO-1 (44 vs. 13%, p<0.001), LAG3 (35 vs. 21%, p=0.008) and IL10 (31 vs. 15%, p=0.002.) Conclusions: Patients with gynecologic cancers have complex and heterogeneous immune landscapes that are distinct from patient to patient and from other solid tumors. High levels of IDO1 and LAG3 suggest that clinical trials with IDO1 inhibitors or LAG3 inhibitors, respectively, may be warranted in gynecologic cancers.

BIOM-03. COMPREHENSIVE GENOMIC AND IMMUNE PROFILING OF NON-SMALL CELL LUNG CANCER BRAIN METASTASES REVEALS LOW TUMOR INFLAMMATION AND ELEVATED CANCER TESTIS ANTIGEN BURDEN

BACKGROUND

Non-small cell lung cancer (NSCLC) accounts for ~50% of brain metastases. We present the genomic and immune biomarker landscape for a cohort with metastatic NSCLC to the brain.

METHODS

We analyzed brain metastases FFPE tissue (n=137; ages 40-85y (mean 65y), 52% female, 48% male) vs. primary sites (n=5533; ages 24-100+y (mean 71y), 51% female, 49% male) for advanced or metastatic NSCLC patients with comprehensive genomic and immune biomarker profiling, including PD-L1 IHC, tumor mutational burden (TMB), Tumor Immunogenic Signature (TIGS), Cell Proliferation (CP), and Cancer Testis Antigen Burden (CTAB).

RESULTS

Genomic alteration (GA) frequency for NSCLC brain metastasis versus primary sites were similar among the most frequently mutated genes except for KRAS which was significantly higher among brain metastases (39.9% vs 25.5%, p&lt; 0.0005). No significant differences were observed for TP53 (50.7% vs 50.2%), STK11 (11.5% vs 10.9%), CDKN2A (10.1% vs 7%), or EGFR (8.0% vs 11.5%). PD-L1 expression for all cases by IHC was not significantly different (mean TPS 29.9% vs 26.3%); however, brain metastases were more likely to be PD-L1 negative (TPS&lt; 1%) (46.3% vs 33.3%, p&lt; 0.005). Conversely, TMB was higher in brain metastases versus primary sites (12.9 vs 10.2 muts/MB, p&lt; 8x10-10), with more TMB-high cases (10 muts/Mb) (57.0% vs 33.5%, p&lt; 3x10-8). Similarly, brain metastases had a higher proportion of CTAB-high cases (68.6% vs 57.6%, p=0.01). The immune response biomarker score, TIGS, was more often weak in brain metastases (52.6% vs 34.0%, p&lt; 9x10-6).

CONCLUSION

In NSCLC, metastatic brain lesions have a larger antigen burden, with increased TMB and CTAB, likely due to the immune privileged nature of the brain, which is reflected in the lower TIGS scores and PD-L1 positivity. Despite lower PD-L1 positivity, NSCLC brain metastases with negative PD-L1 IHC may potentially benefit from immunotherapy strategies given the high TMB and CTAB.

Evaluation of tumor microenvironment and biomarkers of immune checkpoint inhibitor response in metastatic renal cell carcinoma

BACKGROUND

Immunotherapy combinations including ipilimumab and nivolumab are now the standard of care for untreated metastatic renal cell carcinoma (mRCC). Biomarkers of response are lacking to predict patients who will have a favorable or unfavorable response to immunotherapy. This study aimed to use the OmniSeq transcriptome-based platform to develop biomarkers of response to immunotherapy.

METHODS

Two cohorts of patients were retrospectively collected. These included an investigational cohort of patients with mRCC treated with immune checkpoint inhibitor therapy from five institutions, and a subsequent validation cohort of patients with mRCC treated with combination ipilimumab and nivolumab from two institutions (Duke Cancer Institute and Cleveland Clinic Taussig Cancer Center). Tissue-based RNA sequencing was performed using the OmniSeq Immune Report Card on banked specimens to identify gene signatures and immune checkpoints associated with differential clinical outcomes. A 5-gene expression panel was developed based on the investigational cohort and was subsequently evaluated in the validation cohort. Clinical outcomes including progression-free survival (PFS) and overall survival (OS) were extracted by retrospective chart review. Objective response rate (ORR) was assessed by Response Evaluation Criteria in Solid Tumors (RECIST) V.1.1.

RESULTS

The initial investigation cohort identified 86 patients with mRCC who received nivolumab (80%, 69/86), ipilimumab/nivolumab (14%, 12/86), or pembrolizumab (6%, 5/86). A gene expression score was created using the top five genes found in responders versus non-responders (FOXP3, CCR4, KLRK1, ITK, TIGIT). The ORR in patients with high gene expression (GE_high) on the 5-gene panel was 29% (14/48), compared with low gene expression (GE_low) 3% (1/38, χ² p=0.001). The validation cohort was comprised of 62 patients who received ipilimumab/nivolumab. There was no difference between GE_high and GE_low in terms of ORR (44% vs 38.5%), PFS (HR 1.5, 95% CI 0.58 to 3.89), or OS (HR 0.96, 95% CI 0.51 to 1.83). Similarly, no differences in ORR, PFS or OS were observed when patients were stratified by tumor mutational burden (high=top 20%), PD-L1 (programmed death-ligand 1) expression by immunohistochemistry or RNA expression, or CTLA-4 (cytotoxic T-lymphocytes-associated protein 4) RNA expression. The International Metastatic RCC Database Consortium (IMDC) risk score was prognostic for OS but not PFS.

CONCLUSION

A 5-gene panel that was associated with improved ORR in a predominantly nivolumab monotherapy population of patients with mRCC was not predictive for radiographic response, PFS, or OS among patients with mRCC treated with ipilimumab and nivolumab.

Abstract 5137: Cancer testis antigen burden: Pan-cancer distribution and survival implications

Purpose of Study: Cancer testis antigens (CTA) are highly immunogenic genes with the ability to cause cancer-specific immune responses when expressed. Their tumor cell-specific expression makes them a key target of natural T cell response, cancer vaccines, immune checkpoint blockade (ICB), and cell-based immunotherapies in a wide range of tumor types. In this study, we assess the pan-cancer distribution and ICB survival association of CTA burden (CTAB) in real-world solid tumors.

Procedure: Three tumor sample cohorts were studied: 1) a pan-cancer discovery cohort to develop a low- and high-CTAB cutoff (n=5450, 39 tumor types), 2) a TCGA cohort (n=19923, 32 tumor types) used to validate the classifier based on CTAB distribution and serve as a non-ICB-treated population, and 3) an ICB-treated retrospective cohort to validate the classification on overall survival (OS) (n=242, 3 tumor types). The expression levels of 17 CTA were measured using targeted RNA-Seq of FFPE tumor samples and then ranked against a pan-cancer reference population. CTAB was calculated for each sample, cohort and tumor type as the sum of the 17 CTA gene expression ranks. The discovery cohort median CTAB of 171 was used to classify all three cohorts into high- and low-CTAB groups. OS analysis was performed on the TCGA and ICB-treated cohorts using a CoxPH regression model to determine the Hazard Ratio (HR).

Results: The three cohorts demonstrated overlapping single-peak, left-skewed CTAB distribution curves centered at CTAB values between 170 (discovery cohort) and 256 (retrospective cohort). When grouping by tumor types and ordering by median CTAB, the CTAB distributions for tumor types within all three cohorts were comparable. CoxPH regression analysis revealed an association between the CTAB threshold classifier and OS in both the ICB-treated retrospective and non-ICB TCGA cohorts. However, the direction of this association differed between the two cohorts, with high-CTAB samples having better survival (HR=0.936, p=0.076) in the ICB-treated retrospective cohort and worse survival (HR: 1.007, p=0.084) in the non-ICB-treated cohort.

Conclusion: Our studies show that the CTAB distribution was maintained across the discovery and TCGA cohorts and a wide range of tumor types, supporting that the CTAB classifier is valid and histology agnostic. Additionally, when evaluating the ICB and non-ICB-treated cohorts, CTAB demonstrated the ability to predict OS, pointing to the utility of ICB in supporting CTA-specific natural immune response. However, further studies are necessary to verify these mechanisms of response to ICB as well as cancer vaccines and cell-based immunotherapies. Additional validation is needed to establish the predictive utility of CTAB alone and in combination with other immune oncology biomarkers for resistance or response.

Citation Format: R.J. Seager, Erik Van Roey, Shuang Gao, Blake Burgher, Paul DePietro, Mary Nesline, Roger Klein, Shengle Zhang, Jeffrey M. Conroy, Sarabjot Pabla. Cancer testis antigen burden: Pan-cancer distribution and survival implications [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5137.

Abstract 1259: PD-L1 expression by RNA-sequencing and survival from pembrolizumab in non-small cell lung cancer (NSCLC)

PURPOSE: The immunohistochemistry companion diagnostic test for pembrolizumab (IHC 22C3 pharmDx) lacks sensitivity, challenging immunotherapy selection for NSCLC patients with lower levels of expression. Unlike IHC 22C3, which restricts assessment of PD-L1 expression to viable tumor cells as a tumor proportion score (% TPS), mRNA next generation sequencing (RNA-seq) measures PD-L1 expression in the tumor microenvironment for both tumor and inflammatory background cells. RNA-seq previously demonstrated concordance with IHC and may be a robust alternative testing method for multiple tumor types. Here, we sought to optimize PD-L1 RNA-seq cutoff values in NSCLC to improve clinical sensitivity.

PROCEDURE: NSCLC patients included in the study (n=3,465) were tested for PD-L1 expression by IHC 22C3 and clinically validated RNA-seq, measured as % rank (0-100) relative to a reference population based on normalized reads per million (nRPM). Patients were divided into an RNA-seq cut-off discovery cohort (n=3,168), and a test cohort pembrolizumab treated patients. Principal components analysis (PCA) was used to classify patients based on test results and explore cut-off values in the discovery cohort. Kaplan Meier curves and a Cox proportional hazards regression models assessed overall survival (OS) hazard ratios (HR) for RNA-seq versus standard of care IHC cut-offs in the test cohort.

RESULTS: Unsupervised PCA clustering identified three distinct PD-L1 groups separated by combinations of significant over- and under-representation of RNA-seq and IHC result measures from prior testing. The groups were labeled as “low” (rank ≤40), “moderate” (rank 41-73), and “high” (rank ≥74), based on the median RNA-seq rank for each group (+/- 1SD for low and high). Both the low and moderate groups were overrepresented by patients in the PD-L1 IHC low and negative groups. The moderate group was overrepresented by patients with moderately high PD-L1 RNA-seq ranks (median=70), while the low group was overrepresented by patients that were not PD-L1 high by RNA-seq. The high group was overrepresented by patients high for PD-L1 by both IHC and RNA-seq. OS HRs were better for RNA-seq high versus moderate (HR=0.05, CI 0.00-0.63, p=.02), and RNA-seq high versus low (HR=0.16, CI 0.03-0.86, p=.03) groups compared to standard of care IHC 22C3 high versus low groups, (HR=0.21, CI 0.04-1.07, p=.06). Findings were non-significant for the RNA-seq moderate versus low groups, likely due to the limited and disproportionately high number of patients with poor performance status in these groups.

CONCLUSIONS: PD-L1 expression by RNA-seq demonstrated improved clinical sensitivity in predicting OS versus standard of care PD-LI IHC in a pembrolizumab treated NSCLC patient cohort. Additional studies are needed to further define cut-offs in the context of performance status, and better understand immune escape mechanisms in the moderate group.

Citation Format: Mary K. Nesline, Sarabjot Pabla, Yong Hee Lee, Paul DePietro, Amy Early, Roger Klein, Shengle Zhang, Jeffrey Conroy. PD-L1 expression by RNA-sequencing and survival from pembrolizumab in non-small cell lung cancer (NSCLC) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1259.

Comprehensive transcriptomic analysis of immune checkpoint markers in a pancancer cohort: Implications for response and resistance

2555

Background: Although immune checkpoint blockade (ICB) has revolutionized cancer treatment, not all patients with cancer benefit from ICB. One possible explanation for poor responders/resistance is the variable expression level of the target molecules (e.g., PD-1 and PD-L1) in the tumor microenvironment. There are recent or ongoing trials targeting variable pathways for immune evasion (e.g., LAG3 or IDO1). It is therefore of interest to know the expression levels related to variable immune checkpoints so that clinical trials can focus on the patients who can benefit from the cognate treatment. Methods: Overall, 514 patients with various solid tumors seen at the University of San Diego, Moores Center for Personalized Cancer Therapy were analyzed. The expression levels of checkpoint markers (ADORA2A, BTLA, CD276, CTLA4, IDO1, IDO2, LAG3, NOS2, PD-1, PD-L1, PD-L2, PVR, TIGIT, TIM3, VISTA, and VTCN) in the tumor samples were measured through RNA sequencing and normalized to internal housekeeping gene profiles, and ranked from 0 to 100 percentile based on a reference population. The expressions of each checkpoint marker were correlated with cancer types, microsatellite instability (MSI), tumor mutational burden (TMB), and programmed death-ligand 1 (PD-L1) status on immunohistochemistry. Results: In this cohort, 60% were female, median age of 60, and included 30 different tumor types, with colorectal cancer being the most common (27%). The rank values of all checkpoint markers were distributed broadly from 0 to 99 or 100. CD276 and NOS2 had the highest (68th percentile) and lowest (13.5 percentile) median rank values, respectively. When rank values were categorized to “Low” (0-24), “Intermediate” (25-74), and “High” (75-100), 41.6% of patients showed high expression of CD276 while only 13% showed high expression of PD-L1. Each patient had a distinctive protfolio of the categorical expression levels of 16 checkpoint markers. Several checkpoint markers, especially NOS2, showed a significant correlation with cancer type. (median rank values in colorectal, stomach, pancreatic, and breast cancer were 79, 76, 5 and 0 respectively, p < 0.001) Five markers (IDO1, LAG3, PD-1, PD-L1, and TIGIT) showed significant correlation with MSI, while seven markers (CTLA4, IDO1, LAG3, PD-1, PD-L1, PD-L2, and TIGIT) were significantly associated with positive PD-L1 status. However, no significant association was seen based on TMB or tissue-specific grouping of patients. Conclusions: The expression of immune checkpoint markers varies from patient to patient, though transcript expression of several markers correlates with cancer type, MSI, and PD-L1 status. Clinical trials with patient selection based on the expression level of checkpoint markers matched to the corresponding ICB drug are warranted.

Comprehensive genomic and immune profiling (CGIP) treatment patterns and survival in non-small cell lung cancer (NSCLC)

e21167

Background: CGIP analyzes FFPE tumor tissue by DNA/RNA sequencing for SNVs, indels, copy gain/loss, fusions, splice variants, MSI and TMB, along with PD-L1 IHC. A purported advantage of CGIP in NSCLC is the ability to identify targeted and immunotherapy biomarkers to inform clinical management. However, the extent to which CGIP supports treatment decisions and benefits NSCLC patients in various treatment settings is limited. Methods: A retrospective analysis of OmniSeq CGIP results (June 2017-March 2019) and real-world clinical data (through March 2020) for NSCLC patients (n = 300) was performed to evaluate treatment strategies at Roswell Park Comprehensive Cancer Center. Patient targeted and immunotherapies following CGIP were classified as “matched” to biomarker results (established or potentially clinically significant) at the indication level (single or multi-marker results, histology, treatment line) based on AMP/ASCO/CAP guidance for strength of biomarker clinical evidence. We estimated overall survival (OS) from CGIP report date for patients who first received either matched therapy or chemotherapy (and no subsequent matched therapy), and assessed the predictive value of matched therapy for OS in the first or subsequent line setting, adjusting for clinicopathologic covariates. Results: Most CGIP tested patients were female (55%), stage IIIB/IV (89%), ECOG < 2 (83%), non-squamous (86%), treatment naïve (62%), ever smokers (88%). 74% (228) of patients were treated post-CGIP, with 71% receiving at least one matched therapy. Matched therapies received in the frontline setting were supported by the highest (Tier 1A) category of evidence more often than subsequent line therapies (97% vs. 68%). 90% of patients with oncogenic driver mutations received targeted agents (17% of total) and 57% received matched immunotherapy. In the frontline setting, compared to chemotherapy, OS was highest for patients who first received matched targeted therapy (median = 23.4 mo; HR 0.26; p = .004; 95% CI 0.13-0.68) vs matched immunotherapy (median = 17.9 mo; HR 0.38; p = .001; 95% CI 0.21-0.69). Subsequent line, OS was also highest for patients who first received matched targeted therapy (median not est., mean = 27.5 mo; HR 0.20; p = .063; 95% CI 0.04-1.09) vs matched immunotherapy (median = 17.4 mo; HR 0.20; 95% CI 0.04-1.09), however, these differences were non-significant. Conclusions: CGIP supports evidence-based clinical decision making for NSCLC in the first and subsequent line settings and leads to improved survival for patients who receive matched targeted or immunotherapy compared to chemotherapy. Better predictive markers are needed to identify NSCLC patients who are more likely to respond to immunotherapies. Heterogeneity of patient biomarker profiles and treatment strategies over time in real world practice are a challenge to assessing CGIP efficacy.

LAG3 transcriptomic expression correlates with high levels of PD-1, PD-L1, PD-L2, and CTLA-4 checkpoints and with high tumor mutational burden across cancers

2561

Background: Lymphocyte Activation Gene 3 (LAG3) or CD223 is an immune checkpoint that can be found on various T cells: CD4+, CD8+, regulatory T cells (Tregs), natural killer T cells, natural killer cells, and plasmacytoid dendritic cells. The expression of LAG3 molecule acts to increase T-cell exhaustion, leading to decreased tumor killing as well as an increase in immune suppressive cytokine release. Many clinical trials of LAG3 inhibitors have had modest effects, but recent data suggests that the LAG3 antibody relatlimab together with nivolumab (anti-PD1) provided greater benefit than nivolumab alone in patients with melanoma. Methods: The RNA expression levels of 397 genes in various types of solid tumors from 514 patients seen at the UCSD Moores Cancer Center were analyzed at a CLIA-licensed laboratory, OmniSeq (https://www.omniseq.com/). Following removal of germline variants, synonymous variants, indels and SNVs with < 5% VAF, TMB is reported as mutations/megabase. Transcript abundance was normalized to internal housekeeping gene profiles and ranked (0-100 percentile) in a standardized manner to a reference population of 735 tumors spanning 35 histologies. Odds ratio for high LAG3 expression was calculated and Bonferroni corrected for multiple genes and cancer histologies with > 40 samples. Results: A total of 116 (22.6%) tumors had high LAG3 (≥75) across 32 different histologies. Cancers with the highest proportion of LAG3 were neuroendocrine (47%), uterine (43%), sarcoma (33%), breast (31%), ovarian (30%), pancreatic (24%), lung (20%), stomach (16%), and colorectal (15%). There was significant association for high LAG3 with high PD-L1 (adj P < 0.001), high PD-1 (adj P < 0.0014), high PD-L2 (adj P < 0.0014), high CTLA-4 (adj P < 0.0014), TMB ≥10 mt/mb (adj P = 0.0504). There was no significant association between histologies colorectal (adj P = 0.1834), breast (adj P = NS), ovarian (adj P = NS), pancreatic (adj P = NS), or gender (adj P = 0.272). Conclusions: High LAG3 was found in almost a quarter of tumor samples and significantly associated with other immune checkpoints with FDA-approved drugs. Ongoing studies combining LAG3 inhibitors and specific immune checkpoint inhibitors may yield more clinical benefit if individualized immunomic transcript interrogation is undertaken, rather than population-based approaches without employment of rationally combined agents matched to each patient’s cancer.

Comprehensive genomic and immune profiling defines immunotherapy treatment in patients with NSCLC with low PD-L1 IHC

2623

Background: Immune checkpoint inhibitors (ICIs) have emerged as effective treatments in non-small cell lung cancer (NSCLC). While the clinical utility of single agent ICI or in combination with chemotherapy has been well established, there remains an unmet need for the development of biomarkers that can better predict response. To address this need, we developed and applied a combination genomic and immune biomarker strategy to ICI-treated NSCLC patients which identified distinct patient subgroups with differential benefit among single agent or combination ICI treatment strategies. Methods: A discovery cohort (DC) of 5450 tumors across 37 histologies were evaluated by comprehensive genomic and immune profiling of the tumor immune microenvironment. Individual and combination biomarker assessment included PD-L1 IHC, TMB, tumor inflammation (TIGS), cell proliferation (CP) and cancer testis antigen burden (CTAB). From this cohort, combinations of molecular and immune biomarkers were identified and applied to a retrospective cohort (RC) of 225 metastatic NSCLC patients treated with pembrolizumab + chemo or pembrolizumab alone to correlate with response. Comparison of objective response rates (ORR) was performed using Chi-square test. Kaplan-Meir analysis was performed to test for differences in overall survival (OS) and 1-year OS. Results: Unsupervised analysis of the DC revealed four distinct biomarker combination groups that describe underlying tumor immunobiology: tumor dominant (CTAB, TMB, CP High), proliferative (CP High), inflamed (TIGS High), and checkpoint (PDL1, TIGS and TMB High). Application of these biomarker groups to the RC demonstrated significant differences in response to ICI regimens between groups (p = 0.04). Patients in the proliferative group (35.1%, 79/225; median PD-L1 = 20% TPS) treated with single agent pembrolizumab showed a significantly higher ORR (59%; 16/27) compared to pembrolizumab + chemo (27%; 14/52; p = 0.005), significantly improved 1-yr OS (p = 0.03), and trend towards better OS (p = 0.14). Importantly, patients in the inflamed group (16%, 36/225; median PD-L1 = 1% TPS), suggested that pembrolizumab + chemo (ORR 26.1%; 6/23) was not associated with ORR compared to pembrolizumab (ORR 31%; 4/13, p = 0.76), or OS (p = 0.37) and 1-yr OS (p = 0.57). Conclusions: Comprehensive genomic and immune profiling may identify PD-L1 low NSCLC patients who benefit from single agent pembrolizumab. PD-L1 low NSCLC patients with a proliferative phenotype may benefit from single agent pembrolizumab, whereas PD-L1 low cases with an inflamed phenotype may benefit from both single agent and combination pembrolizumab. Although further clinical validation of these predictive biomarker combinations is required, this data-driven approach demonstrates the potential to provide treatment decision support when selecting an ICI therapeutic strategy in lung cancer.

Obesity-Specific Association of Statin Use and Reduced Risk of Recurrence of Early Stage NSCLC

Introduction

Statins, used for their lipid-lowering activity, have anti-inflammatory and anticancer properties as well. We evaluated this potential benefit of statin use in patients with NSCLC.

Methods

All 613 patients with pathologic stage 1 or 2 NSCLC who had lobectomy without neoadjuvant therapy at our institution during 2008 to 2015 were included. Association between presurgery statin use and overall survival and recurrence-free survival (RFS) was analyzed using Cox proportional hazards regression. Association of statin use with tumor transcriptome was evaluated in another 350 lung cancer cases.

Results

Univariable analyses did not reveal a statistically significant association of statin use with either overall survival or RFS, with hazard ratio equals to 1.19 and 0.70 (Wald p = 0.28 and 0.09), respectively. In subgroup analyses, significantly improved RFS was found in statin users, but only in overweight/obese patients (body mass index [BMI] > 25; n = 422), with univariable and multivariable hazard ratio of 0.49 and 0.46 (p = 0.005 and 0.002), respectively, but not in patients with BMI less than or equal to 25 (n = 191; univariable p = 0.21). Transcriptomes of tumor statin users had high expression of tumoricidal genes such as granzyme A and interferon-γ compared with those of nonusers among high- but not low-BMI patients with lung cancer.

Conclusions

Our study suggests that statins may improve the outcome of early stage NSCLC but only in overweight or obese patients. This benefit may stem from a favorable reprogramming of the antitumor immune response that statins perpetrate specifically in the obese.

Tumor Inflammation, Obesity, and Proliferative Status as Biomarkers in Gastroesophageal Adenocarcinoma

Recent epidemiological studies have shown that obesity, typically measured by increased body mass index (BMI), is associated with an increased risk of gastroesophageal adenocarcinoma (GEAC), but the contributing molecular and immune mechanisms remain unknown. Since obesity is known to promote chronic inflammation, we hypothesized that obesity leads to inflammation-related immune dysfunction, which can be reversed by immune-modulating therapy. To test our hypothesis, we examined the clinical and molecular data from advanced GEAC patients. To this end, 46 GEAC tumors were evaluated for biomarkers representing tumor inflammation, cell proliferation, and PD-L1 expression. A CoxPH regression model with potential co-variates, followed by pairwise post hoc analysis, revealed that inflammation in the GEAC tumor microenvironment is associated with improved overall survival, regardless of BMI. We also observed a significant association between cell proliferation and progression-free survival in overweight individuals who received immune-modulating therapy. In conclusion, our data confirm the role of the immune system in the natural course of GEAC and its responses to immunotherapies, but do not support the role of BMI as an independent clinically relevant biomarker in this group of patients.

A scalable high-throughput targeted next-generation sequencing assay for comprehensive genomic profiling of solid tumors

Timely and accurate identification of molecular alterations in solid tumors is essential for proper management of patients with advanced cancers. This has created a need for rapid, scalable comprehensive genomic profiling (CGP) systems that detect an increasing number of therapeutically-relevant variant types and molecular signatures. In this study, we assessed the analytical performance of the TruSight Oncology 500 High-Throughput assay for detection of somatic alterations from formalin-fixed paraffin-embedded tissue specimens. In parallel, we developed supporting software and automated sample preparation systems designed to process up to 70 clinical samples in a single NovaSeq 6000TM sequencing run with a turnaround time of <7 days from specimen receipt to report. The results demonstrate that the scalable assay accurately and reproducibly detects small variants, copy number alterations, microsatellite instability (MSI) and tumor mutational burden (TMB) from 40ng DNA, and multiple gene fusions, including known and unknown partners and splice variants from 20ng RNA. 717 tumor samples and reference materials with previously known alterations in 96 cancer-related genes were sequenced to evaluate assay performance. All variant classes were reliably detected at consistent and reportable variant allele percentages with >99% overall accuracy and precision. Our results demonstrate that the high-throughput CGP assay is a reliable method for accurate detection of molecular alterations in support of precision therapeutics in oncology. The supporting systems and scalable workflow allow for efficient interpretation and prompt reporting of hundreds of patient cancer genomes per week with excellent analytical performance.

Aligning tumor mutational burden (TMB) quantification across diagnostic platforms: phase II of the Friends of Cancer Research TMB Harmonization Project

BACKGROUND

Tumor mutational burden (TMB) measurements aid in identifying patients who are likely to benefit from immunotherapy; however, there is empirical variability across panel assays and factors contributing to this variability have not been comprehensively investigated. Identifying sources of variability can help facilitate comparability across different panel assays, which may aid in broader adoption of panel assays and development of clinical applications.

MATERIALS AND METHODS

Twenty-nine tumor samples and 10 human-derived cell lines were processed and distributed to 16 laboratories; each used their own bioinformatics pipelines to calculate TMB and compare to whole exome results. Additionally, theoretical positive percent agreement (PPA) and negative percent agreement (NPA) of TMB were estimated. The impact of filtering pathogenic and germline variants on TMB estimates was assessed. Calibration curves specific to each panel assay were developed to facilitate translation of panel TMB values to whole exome sequencing (WES) TMB values.

RESULTS

Panel sizes >667 Kb are necessary to maintain adequate PPA and NPA for calling TMB high versus TMB low across the range of cut-offs used in practice. Failure to filter out pathogenic variants when estimating panel TMB resulted in overestimating TMB relative to WES for all assays. Filtering out potential germline variants at >0% population minor allele frequency resulted in the strongest correlation to WES TMB. Application of a calibration approach derived from The Cancer Genome Atlas data, tailored to each panel assay, reduced the spread of panel TMB values around the WES TMB as reflected in lower root mean squared error (RMSE) for 26/29 (90%) of the clinical samples.

CONCLUSIONS

Estimation of TMB varies across different panels, with panel size, gene content, and bioinformatics pipelines contributing to empirical variability. Statistical calibration can achieve more consistent results across panels and allows for comparison of TMB values across various panel assays. To promote reproducibility and comparability across assays, a software tool was developed and made publicly available.

80 Cancer testis antigen burden: A novel predictive biomarker for immunotherapy in solid tumors

Background

When expressed in cancer cells, cancer testis antigens (CTAs) are highly immunogenic and have the capacity to elicit cancer-specific immune responses in diverse malignancies. With their expression limited to tumor cells, CTAs have become a prime target of natural T cell response, immune cell-based therapy, and cancer vaccines. In this study, we investigated CTA burden in real-world clinical tumors spanning multiple histologies, revealing a novel prognostic gene expression-based biomarker.

Methods

Targeted RNA-seq was performed on 5450 FFPE tumors representing 39 histologic types, predominantly composed of lung cancer (40.4%) followed by colorectal cancer (10.6%) and breast cancer (8.6%). Using an amplicon-based NGS approach, expression levels of 17 CTA genes were ranked against a reference population. Cancer Testis Antigen Burden (CTAB) was calculated as the sum of the gene expression rank for each CTA gene. The median CTAB of ≥171 was used as cutoff for CTAB High versus Low classification. We estimated Pearson’s correlation for all CTA genes to discover co-expression patterns between CTAs and histologies. Overall survival (OS) analysis was performed using CoxPh regression model whereas response analysis was performed using logistic regression model with p-values reported.

Results

Within the tumor samples, CTAB values ranged from 0–1700, with kidney cancer demonstrating overall lowest mean CTAB (110) and melanoma the highest (550). NSCLC had an average CTAB of 283. In an immune checkpoint blockade treated retrospective cohort of 110 NSCLC patients, High CTAB showed better OS compared to Low CTA (HR: 0.55, p=0.07). Additionally, when combined with tumor inflammation and cell proliferation biomarkers, highly inflamed but poorly proliferative tumors with High CTAB had improved OS (HR: 0.27, p=0.05). No significant association with response was detected

Conclusions

Our studies show that co-expression of multiple CTA genes occurs in many tumor types and can be reliably detected using a targeted RNA-seq approach. Utilization of this co-expression pattern to calculate CTAB reveals tumor-type associated signatures, which in a small NSCLC cohort is associated with the overall survival. The findings suggest that these immunogenic antigens expose the tumor cells to natural or immunotherapy augmented cell-based immune response, and that CTAB is a potential predictive marker for therapeutic response to checkpoint inhibitors. Further studies are needed to establish the predictive value in other tumor types, as well as the role of CTAB in immune cell therapies and vaccinations.

77 Prevalence of secondary immunotherapeutic targets in the absence of established immune biomarkers in solid tumors

Background

Immune checkpoint inhibitor-based therapies have achieved impressive success in the treatment of several cancer types. Predictive immune biomarkers, including PD-L1, MSI and TMB are well established as surrogate markers for immune evasion and tumor-specific neoantigens across many tumors. Positive detection across cancer types varies, but overall ~50% of patients test negative for these primary immune markers.1 In this study, we investigated the prevalence of secondary immune biomarkers outside of PD-L1, TMB and MSI.

Methods

Comprehensive genomic and immune profiling, including PD-L1 IHC, TMB, MSI and gene expression of 395 immune related genes was performed on 6078 FFPE tumors representing 34 cancer types, predominantly composed of lung cancer (36.7%), colorectal cancer (11.9%) and breast cancer (8.5%). Expression levels by RNA-seq of 36 genes targeted by immunotherapies in solid tumor clinical trials, identified as secondary immune biomarkers, were ranked against a reference population. Genes with a rank value ≥75th percentile were considered high and values were associated with PD-L1 (positive ≥1%), MSI (MSI-H or MSS) and TMB (high ≥10 Mut/Mb) status. Additionally, secondary immune biomarker status was segmented by tumor type and cancer immune cycle roles.

Results

In total, 41.0% of cases were PD-L1+, 6.4% TMB+, and 0.1% MSI-H. 12.6% of cases were positive for >2 of these markers while 39.9% were triple negative (PD-L1-/TMB-/MSS). Of the PD-L1-/TMB-/MSS cases, 89.1% were high for at least one secondary immune biomarker, with 69.3% having ≥3 markers. PD-L1-/TMB-/MSS tumor types with ≥50% prevalence of high secondary immune biomarkers included brain, prostate, kidney, sarcoma, gallbladder, breast, colorectal, and liver cancer. High expression of cancer testis antigen secondary immune biomarkers (e.g., NY-ESO-1, LAGE-1A, MAGE-A4) was most commonly observed in bladder, ovarian, sarcoma, liver, and prostate cancer (≥15%). Tumors demonstrating T-cell priming (e.g., CD40, OX40, CD137), trafficking (e.g., TGFB1, TLR9, TNF) and/or recognition (e.g., CTLA4, LAG3, TIGIT) secondary immune biomarkers were most represented by kidney, gallbladder, and sarcoma (≥40%), with melanoma, esophageal, head & neck, cervical, stomach, and lung cancer least represented (≥15%).

Conclusions

Our studies show comprehensive tumor profiling that includes gene expression can detect secondary immune biomarkers targeted by investigational therapies in ~90% of PD-L1-/TMB-/MSS cases. While genomic profiling could also provide therapeutic choices for a percentage of these patients, detection of secondary immune biomarkers by RNA-seq provides additional options for patients without a clear therapeutic path as determined by PD-L1 testing and genomic profiling alone.

Reference

Huang R S P, Haberberger J, Severson E, et al. A pan-cancer analysis of PD-L1 immunohistochemistry and gene amplification, tumor mutation burden and microsatellite instability in 48,782 cases. Mod Pathol 2021;34: 252–263.

70 Novel immunotherapeutic targets in cancer of unknown primary (CUP)

Background

Cancer of unknown primary (CUP) is a rare tumor type accounting for 2% of solid cancers. In the subset of CUP cases where tumor of origin is posited and treated as such, no clear clinical benefit has been demonstrated. Furthermore, CUP patients treated by empiric platinum-based regimens have low response and survival rates of approximately 20%.1 2 Support of tissue-agnostic marker-directed immunotherapy is growing because it targets the immune system rather than the tumor, with some efficacy evidence emerging for CUP.3 Identifying new targets for immunotherapeutic opportunities in this heterogeneous and difficult to treat patient group is a critical unmet need.

Methods

Comprehensive genomic and immune marker profiling by NGS4 was performed on FFPE tissue for CUP tumors (n=298) as indicated by physicians’ test orders from >100 clinical practice sites. Histology was verified by a molecular pathologist as part of pre-analytic test quality control, with cases representing tumors with adenocarcinoma (58%), carcinoma (26%), squamous (10%), and neuroendocrine (6%) histologic features. RNA-expression levels of immune genes that are current targets in non-CUP immunotherapy clinical trials (n=36) were ranked against a reference population (≥75th percentile=high), and described by histologic type, along with PD-L1 IHC (22C3) expression, tumor mutational burden (TMB) and genomic variants.

Results

90% of all CUP tumors had at least 1 highly expressed immune gene target in active immunotherapy trials, with the most frequent being TGFB1 (47%) and CCL2 (39%). 55% of CUP tumors were PD-L1 IHC 22C3 positive (>=1% TPS), and 21% had high TMB (>=10 mut/Mb) in CUP tumors with neuroendocrine (32%), carcinoma (30%), squamous cell (21%), and adenocarcinoma (17%) histologic features. Overall, 26% of CUP patient tumors, mostly adenocarcinomas (28%) and carcinomas (27%), harbored genomic variants (n=77) with FDA approved targeted therapies in other tumor types. The most frequently immunogenic CUP tumors were carcinomas, showing high RNA-seq expression of 26/36 genes in at least 20% of patients, most represented by CD20, CD27, TLR8, and PD-L1. High expression of CD40, CSF1R, TIM3, and VISTA was most common in adenocarcinomas. Squamous cell carcinomas were relatively immunogenic, with frequent high expression of 17/36 immune genes, uniquely including MAGEA4. Neuroendocrine tumors were the least immunogenic, with frequent high expression in only 4/36 genes, including ADORA2A (42%) and MAGEA1 (37%).

Conclusions

CUP tumors diversely express both standard marker and novel immunotherapeutic targets based on histology and may benefit from selective access to clinical trials for these therapies.

References

National Comprehensive Cancer Network. NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines®) Occult Primary (Cancer of Unknown Primary [CUP]), Version 2.2021. Fort Washington, Pennsylvania: National Comprehensive Cancer Network; 2021. https://www.nccn.org/professionals/physician_gls/pdf/occult.pdf.

Laprovitera N, Riefolo M, Ambrosini E, Klec C, Pichler M, Ferracin M. Cancer of unknown primary: Challenges and progress in clinical management. Cancers (Basel) 2021;13(3):1–30. doi:10.3390/cancers130304513.

Naing A, Meric-Bernstam F, Stephen B, et al. Phase 2 study of pembrolizumab in patients with advanced rare cancers. J Immunother Cancer 2020;8(1):e000347. doi:10.1136/jitc-2019-0003474.

Conroy JM, Pabla S, Glenn ST, et al. Analytical validation of a next-generation sequencing assay to monitor immune responses in solid tumors. J Mol Diagnostics 2018;20(1):95–109. doi:10.1016/j.jmoldx.2017.10.001

Integration of tumor inflammation, cell proliferation, and traditional biomarkers improves prediction of immunotherapy resistance and response

BACKGROUND

Contemporary to the rapidly evolving landscape of cancer immunotherapy is the equally changing understanding of immune tumor microenvironments (TMEs) which is crucial to the success of these therapies. Their reliance on a robust host immune response necessitates clinical grade measurements of immune TMEs at diagnosis. In this study, we describe a stable tumor immunogenic profile describing immune TMEs in multiple tumor types with ability to predict clinical benefit from immune checkpoint inhibitors (ICIs).

METHODS

A tumor immunogenic signature (TIGS) was derived from targeted RNA-sequencing (RNA-seq) and gene expression analysis of 1323 clinical solid tumor cases spanning 35 histologies using unsupervised analysis. TIGS correlation with ICI response and survival was assessed in a retrospective cohort of NSCLC, melanoma and RCC tumor blocks, alone and combined with TMB, PD-L1 IHC and cell proliferation biomarkers.

RESULTS

Unsupervised clustering of RNA-seq profiles uncovered a 161 gene signature where T cell and B cell activation, IFNg, chemokine, cytokine and interleukin pathways are over-represented. Mean expression of these genes produced three distinct TIGS score categories: strong (n = 384/1323; 29.02%), moderate (n = 354/1323; 26.76%), and weak (n = 585/1323; 44.22%). Strong TIGS tumors presented an improved ICI response rate of 37% (30/81); with highest response rate advantage occurring in NSCLC (ORR = 36.6%; 16/44; p = 0.051). Similarly, overall survival for strong TIGS tumors trended upward (median = 25 months; p = 0.19). Integrating the TIGS score categories with neoplastic influence quantified via cell proliferation showed highly proliferative and strong TIGS tumors correlate with significantly higher ICI ORR than poorly proliferative and weak TIGS tumors [14.28%; p = 0.0006]. Importantly, we noted that strong TIGS and highly [median = not achieved; p = 0.025] or moderately [median = 16.2 months; p = 0.025] proliferative tumors had significantly better survival compared to weak TIGS, highly proliferative tumors [median = 7.03 months]. Importantly, TIGS discriminates subpopulations of potential ICI responders that were considered negative for response by TMB and PD-L1.

CONCLUSIONS

TIGS is a comprehensive and informative measurement of immune TME that effectively characterizes host immune response to ICIs in multiple tumors. The results indicate that when combined with PD-L1, TMB and cell proliferation, TIGS provides greater context of both immune and neoplastic influences on the TME for implementation into clinical practice.

Immune profiling and immunotherapeutic targets in pancreatic cancer

Background

Immunotherapeutic approaches for pancreatic ductal adenocarcinoma (PDAC) are less successful as compared to many other tumor types. In this study, comprehensive immune profiling was performed in order to identify novel, potentially actionable targets for immunotherapy.

Methods

Formalin-fixed paraffin embedded (FFPE) specimens from 68 patients were evaluated for expression of 395 immune-related markers (RNA-seq), mutational burden by complete exon sequencing of 409 genes, PD-L1 expression by immunohistochemistry (IHC), pattern of tumor infiltrating lymphocytes (TILs) infiltration by CD8 IHC, and PD-L1/L2 copy number by fluorescent in situ hybridization (FISH).

Results

The seven classes of actionable genes capturing myeloid immunosuppression, metabolic immunosuppression, alternative checkpoint blockade, CTLA-4 immune checkpoint, immune infiltrate, and programmed cell death 1 (PD-1) axis immune checkpoint, discerned 5 unique clinically relevant immunosuppression expression profiles (from most to least common): (I) combined myeloid and metabolic immunosuppression [affecting 25 of 68 patients (36.8%)], (II) multiple immunosuppressive mechanisms (29.4%), (III) PD-L1 positive (20.6%), (IV) highly inflamed PD-L1 negative (10.3%); and (V) immune desert (2.9%). The Wilcoxon rank-sum test was used to compare the PDAC cohort with a comparison cohort (n=1,416 patients) for the mean expressions of the 409 genes evaluated. Multiple genes including TIM3, VISTA, CCL2, CCR2, TGFB1, CD73, and CD39 had significantly higher mean expression versus the comparison cohort, while three genes (LAG3, GITR, CD38) had significantly lower mean expression.

Conclusions

This study demonstrates that a clinically relevant unique profile of immune markers can be identified in PDAC and be used as a roadmap for personalized immunotherapeutic decision-making strategies.

Abstract 970: Single-cell mRNA sequencing analysis of the synergistic impact of double-stranded RNA (dsRNA) and IFNα on human monocyte-derived macrophages

Purpose of Study: Single-cell mRNAseq (scRNAseq) is a promising technology allowing for unbiased analysis of gene expression at the cellular level. In this study, scRNAseq was used to identify cellular sub-types and differential gene expression functional units in monocyte-derived macrophages in response to double-stranded RNA (dsRNA, viral mimic, TLR3 ligand), IFNα or their combination.

Procedure: Human monocyte-derived macrophages were cultured overnight in the absence (U) or presence of dsRNA (rintatolimod/Ampligen-A), IFNα (I) or their combination (IA), which we previously identified as synergistic in induction of chemokines attracting CTLs, Th1 and NK cells. The cells were harvested after 1 day, captured at the single-cell level and immobilized in a vertical flow array chip (VFAC), which contains 100-microchambers packed with 105 beads immobilizing 1010 oligo(dT) probes with unique cell-ID, UMI, and PCR-tags. Each single cell was captured and lysed on the small hole (3-micro meter in diameter) above the microchamber on the VFAC and cDNA libraries were synthesized and tagged with unique cell-IDs post mRNAs hybridization. ScRNAseq using a custom 94- gene inflammation RNA-seq panel was then performed. Post-clustering (Scanpy), unsupervised cell-type identification (louvain), and downstream analyses were performed on the gene expression data to determine impact of A, I and IA treatment on the cellular composition of the induced macrophages.

Results: PCA and unsupervised clustering revealed sample groups with distinct phenotypic signatures. The analyses revealed the expected synergy between the dsRNA and IFNα in the induction of CXCR3- and CCR5-binding chemokines, but antagonism in the induction of Treg attractants. Unexpectedly, the single cell analyses revealed striking heterogeneity of the responses of the individual myeloid cells within the morphologically uniform macrophage population activated by the individual stimuli and their IA combination.

Conclusion: scRNAseq was able to identify distinct single-cell macrophage phenotypes caused by induction of dsRNA and IFNα. Of the 5 subclusters identified, inducement by IFNα alone or in combination with TLR3 identified subsets of cell populations representing lineage and activation markers. These unexpected observations facilitate the identification of intracellular signaling pathways underlying the heterogenous response of individual myeloid cells to exogenous and endogenous activators, helping to develop improved vaccine adjuvants and cancer immunotherapies.

Citation Format: Vincent Giamo, Melissa Grimm, Sarabjot Pabla, Ellen Karasik, Jesse Luce, Sean T. Glenn, Jeffrey Conroy, Jeffrey Conroy, Barbara Foster, Kiyomi Taniguchi, Pawel Kalinski, Masataka Shirai. Single-cell mRNA sequencing analysis of the synergistic impact of double-stranded RNA (dsRNA) and IFNα on human monocyte-derived macrophages [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 970.

Proliferative potential and response to nivolumab in clear cell renal cell carcinoma patients

Background

Biomarkers predicting immunotherapy response in metastatic renal cell cancer (mRCC) are lacking. PD-L1 immunohistochemistry is a complementary diagnostic for immune checkpoint inhibitors (ICIs) in mRCC, but has shown minimal clinical utility and is not used in routine clinical practice.

Methods

Tumor specimens from 56 patients with mRCC who received nivolumab were evaluated for PD-L1, cell proliferation (targeted RNA-seq), and outcome.

Results

For 56 patients treated with nivolumab as a standard of care, there were 2 complete responses and 8 partial responses for a response rate of 17.9%. Dividing cell proliferation into tertiles, derived from the mean expression of 10 proliferation-associated genes in a reference set of tumors, poorly proliferative tumors (62.5%) were more common than moderately (30.4%) or highly proliferative (8.9%) counterparts. Moderately proliferative tumors were enriched for PD-L1 positive (41.2%), compared to poorly proliferative counterparts (11.4%). Objective response for moderately proliferative (29.4%) tumors was higher than that of poorly (11.4%) proliferative counterparts, but not statistically significant (p = .11). When cell proliferation and negative PD-L1 tumor proportion scores were combined statistically significant results were achieved (p = .048), showing that patients with poorly proliferative and PD-L1 negative tumors have a very low response rate (6.5%) compared to moderately proliferative PD-L1 negative tumors (30%).

Conclusions

Cell proliferation has value in predicting response to nivolumab in clear cell mRCC patients, especially when combined with PD-L1 expression. Further studies which include the addition of progression-free survival (PFS) along with sufficiently powered subgroups are required to further support these findings.

Tumor inflammatory signature as a biomarker of response to immunotherapy in lung cancer

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Background: Tumor Inflammation signatures (TIS) comprising multiple immune genes have been shown to enrich for response to ICI. To study this immune phenotype in a large cohort of clinically evaluated patients, we studied gene expression data for a stable pan-cancer tumor inflammation profile and clinical response to ICI. Methods: 1323 FFPE tumors from 35 histologies were tested by RNA-seq, PD-L1 IHC and DNA-seq for TMB. Unsupervised analysis of the RNA-seq data revealed a cluster of 160 genes which separated inflamed from non-inflamed tumor microenvironments (TME). A TIS, algorithmically defined as the mean mRNA expression of the 160 genes was developed with each tumor assigned into a weak, moderate or strong inflammation group. PD-L1 IHC was performed using DAKO 22C3 antibody and considered positive if TPS ≥1%. TMB > 10 mut/Mb was considered high. The TIS, PD-L1 and TMB were independently applied to 110 NSCLC cases for association with ORR to ICIs by RECIST criterion. Results: Unsupervised clustering identified 3 inflammation clusters in the 1323 samples; inflamed (n = 439; 33.2%), borderline (n = 467; 35.3%) and non-inflamed (n = 417; 31.5%). 160 genes are over-represented by T & B-cell activation, IFNg, chemokine, cytokine and interleukin pathways. The TIS algorithm results in an inflammatory score that leads to 3 distinct groups of strong (n = 384; 29.0%), moderate (n = 354; 26.8%) and weak (n = 585; 44.2%) inflammation. Strongly inflamed tumors are over-represented by PD-L1+ tumors (240/384) whereas weakly inflamed tumors are significantly under-represented by PD-L1+ tumors (369/585; p = 1.02e-14). Strongly inflamed tumors presented with improved ORR to ICI in NSCLC (36.6%; 16/44; p = 0.051). Similar results were observed for overall survival for strongly inflamed tumors (median = 16 months; p = 0.0012) vs. weakly inflamed tumors (median = 8 months). ORR for PD-L1+ 33.96% (p = 0.026) and TMB high 21.43% (p = 0.83) were observed. Conclusions: Concurrent measurement of multiple markers led to a comprehensive, stable TIS that predicts host immune response. A strongly inflamed TIS was associated with higher ORR versus single biomarker PD-L1 and TMB in NSCLC.

Inflammation and cell proliferation signatures: Implications for response to immune checkpoint inhibition therapies

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Background: Progress in unraveling the complex tumor immune microenvironment (TIME) has aided our understanding of the host immune response to ICI therapies. To gain further insight, we associate a 160-gene tumor inflammation signature (TIS) with cell proliferation status and response to ICI. Methods: 242 FFPE tumor samples from lung, RCC and melanoma were evaluated by RNA-seq to measure expression levels of 394 immune related genes. TIS (weak, moderate, strong) and cell proliferation status (poor, moderate, high) were determined by algorithmic analysis of selected gene pathways. All cases were evaluated for association with ORR to ICIs using RECIST criterion. Furthermore, 13 pre-post ICI treated biopsy pairs were studied to understand the dynamics of these signatures following treatment. Results: In both weakly and moderately inflamed tumors, ORR was highest in moderately proliferative tumors 32.6% (15/46) and 37.8% (14/37), respectively (Table). Surprisingly, in strongly inflamed tumors, both highly and moderately proliferative tumors had a high response rate of 55% (11/20) and 43.2% (16/37), whereas poorly proliferative tumors have a significantly lower response rate of 12.5% (3/24; p= 0.03). 6 of 13 pre-post ICI treated cases demonstrated increased inflammation post treatment, with 83% (5/6) demonstrating concurrent decrease in cell proliferation. Conclusions: Together, TIS and cell proliferation predict response to ICI in NSCLC, RCC and melanoma. The data suggests that in strongly inflamed and highly proliferative tumors, the cell proliferation signal could be attributed to antigen stimulated T-cell proliferation, whereas in other categories of inflammation, moderately proliferative tumors contain signal from both immune cells and tumor cells. Further studies are required to determine the relationship between these signatures in hot and cold tumors. [Table: see text]

Development and analytical validation of a next-generation sequencing based microsatellite instability (MSI) assay

Background

We have developed and analytically validated a next-generation sequencing (NGS) assay to classify microsatellite instability (MSI) in formalin-fixed paraffin-embedded (FFPE) tumor specimens.

Methodology

The assay relies on DNA-seq evaluation of insertion/deletion (indel) variability at 29 highly informative genomic loci to estimate MSI status without the requirement for matched-normal tissue. The assay has a clinically relevant five-day turnaround time and can be conducted on as little as 20 ng genomic DNA with a batch size of up to forty samples in a single run.

Results

The MSI detection method was developed on a training set (n = 94) consisting of 22 MSI-H, 24 MSS, and 47 matched normal samples and tested on an independent test set of 24 MSI-H and 24 MSS specimens. Assay performance with respect to accuracy, reproducibility, precision as well as control sample performance was estimated across a wide range of FFPE samples of multiple histologies to address pre-analytical variability (percent tumor nuclei), and analytical variability (batch size, run, day, operator). Analytical precision studies demonstrated that the assay is highly reproducible and accurate as compared to established gold standard PCR methodology and has been validated through NYS CLEP.

Significance

This assay provides clinicians with robust and reproducible NGS-based MSI testing without the need of matched normal tissue to inform clinical decision making for patients with solid tumors.

Body Mass Index Influences the Salutary Effects of Metformin on Survival After Lobectomy for Stage I NSCLC

INTRODUCTION

Metformin, a common medication used in the treatment of diabetes mellitus is known to have anticancer effects. We hypothesized that the salutary effect of metformin on the survival of patients with stage I NSCLC is influenced by body mass index (BMI).

METHODS

Patients undergoing lobectomy for stage I NSCLC without neoadjuvant therapy were included. Univariate and multivariate survival analyses to examine the association between metformin use and overall survival (OS), disease-specific survival (DSS), and recurrence-free survival were performed, stratified by BMI (>25 kg/m² and ≤25 kg/m²). Expression of immune checkpoints in patients on metformin and not was performed in a separate cohort of 205 patients with advanced disease.

RESULTS

Four hundred thirty-four stage I patients (including 74 metformin users) were deemed eligible for analysis. Univariate and multivariate analysis revealed an association between metformin use and OS (hazard ratio [HR] = 0.52; p = 0.04) as well as DSS (HR = 0.21; p = 0.04) but not recurrence-free survival (HR = 0.67; p = 0.33) in high-BMI patients only. In a separate cohort of 205 patients with tumors of all stages (including 35 metformin users), downregulation of immune checkpoint gene expression (programmed cell death 1, cytotoxic T-lymphocyte associated protein 4, B and T lymphocyte associated, CD27 molecule, lymphocyte activating 3, and inducible T cell costimulator) in metformin users was seen only in high-BMI patients, with upregulation of these genes seen in low-BMI patients with metformin use.

CONCLUSIONS

Metformin use may be associated with better OS and DSS only in high-BMI patients. This hypothesis is supported by gene expression data of immune checkpoint genes in metformin users using a separate cohort of advanced-stage tumors. Further studies examining the interaction of BMI with metformin in NSCLC are worthwhile.

Evaluation of tumor microenvironment and biomarkers of immune checkpoint inhibitor (ICI) response in metastatic renal cell carcinoma (mRCC)

2595

Background: ICIs are now standard of care for mRCC; however, there are few biomarkers to predict ICI response. Recent data from atezolizumab/bevacizumab trials in mRCC suggest tumors with high Teffhigh/PD-L1+ are more likely to respond to ICI. Here, we use two gene panels as well as other inflammation markers in the tumor microenvironment to correlate with ICI responses. Methods: This multicenter study evaluated 86 patients (pts) with mRCC treated with ICIs. FFPE tumor samples were evaluated by RNA sequencing for Teff status. Two gene panels were analyzed: a Teff Gene Panel (CD8, CD27, IFNG, GZMA, GZMB, PRF1, EOMES, CXCL9, CXCL10, CXCL11, CD274, CTLA4, FOXP3, TIGIT, IDO1, PSMB9, TAP1) and a 5-Gene panel (FOXP3, CCR4, KLRK1, ITK, and TIGIT) based on the gene expression pattern of tumors in our cohort. Objective response rates (ORRs, defined as CRs and PRs) were correlated with PD-L1 status (positivity was defined as ≥1% TPS based on Dako 22C3 IHC assay), and TMB (0-10, 10-20, ≥20 mut/Mb), and tumor inflammation (high CD8 expression compared to a large reference population). Best responses to ICI was determined by an expert radiologist using RECIST 1.1 criteria. Inflamed tumor status, Teff gene panel, 5-gene panel, PD-L1 status, and TMB were associated with ORR and tested using a chi-squared test with Yates’s continuity correction. Results: ORR was 50% (4/8) for PD-L1 positive pts and 14% (9/65) for PD-L1 negative pts (p = 0.042). The majority of tumors (95%, 82/86) had TMB < 10 mut/mb. 43 pts (50%) were classified as Teffhigh and 43 pts were classified as Tefflow. ORR was 23% (10/43) in the Teffhigh cohort and 12% (5/43) in the Tefflow cohort (p = 0.256). ORR was 31% (14/45) in the 5-Gene high cohort and 2% (1/41) in the 5-Gene low cohort (p = 0.001). Conclusions: TMB and tumor inflammation based on CD8 did not reliably predict for objective responses in this study of mRCC pts treated with ICIs. Gene expression signatures provide a more comprehensive evaluation of the tumor microenvironment and may lead to better predictive biomarkers for ICI response than individual biomarkers such as PD-L1, TMB, or CD8 expression.

Validation of Melanoma Immune Profile (MIP), a Prognostic Immune Gene Prediction Score for Stage II-III Melanoma

PURPOSE

Biomarkers are needed to stratify patients with stage II-III melanoma for clinical trials of adjuvant therapy because, while immunotherapy is protective, it also confers the risk of severe toxicity. We previously defined and validated a 53-immune gene melanoma immune profile (MIP) predictive both of distant metastatic recurrence and of disease-specific survival (DSS). Here, we test MIP on a third independent population.

EXPERIMENTAL DESIGN

A retrospective cohort of 78 patients with stage II-III primary melanoma was analyzed using the NanoString assay to measure expression of 53 target genes, and MIP score was calculated. Statistical analysis correlating MIP with DSS, overall survival, distant metastatic recurrence, and distant metastasis-free interval was performed using ROC curves, Kaplan-Meier curves, and standard univariable and multivariable Cox proportional hazards models.

RESULTS

MIP significantly distinguished patients with distant metastatic recurrence from those without distant metastatic recurrence using ROC curve analysis (AUC = 0.695; P = 0.008). We defined high- and low-risk groups based on the cutoff defined by this ROC curve and find that MIP correlates with both DSS and overall survival by ROC curve analysis (AUC = 0.719; P = 0.004 and AUC = 0.698; P = 0.004, respectively). Univariable Cox regression reveals that a high-risk MIP score correlates with DSS (P = 0.015; HR = 3.2).

CONCLUSIONS

MIP identifies patients with low risk of death from melanoma and may constitute a clinical tool to stratify patients with stage II-III melanoma for enrollment in clinical trials.