Tumor Intrinsic Subtypes and Gene Expression Signatures in Early-Stage ERBB2/HER2-Positive Breast Cancer: A Pooled Analysis of CALGB 40601, NeoALTTO, and NSABP B-41 Trials

Importance

Biologic features may affect pathologic complete response (pCR) and event-free survival (EFS) after neoadjuvant chemotherapy plus ERBB2/HER2 blockade in ERBB2/HER2-positive early breast cancer (EBC).

Objective

To define the quantitative association between pCR and EFS by intrinsic subtype and by other gene expression signatures in a pooled analysis of 3 phase 3 trials: CALGB 40601, NeoALTTO, and NSABP B-41.

Design, Setting, and Participants

In this retrospective pooled analysis, 1289 patients with EBC received chemotherapy plus either trastuzumab, lapatinib, or the combination, with a combined median follow-up of 5.5 years. Gene expression profiling by RNA sequencing was obtained from 758 samples, and intrinsic subtypes and 618 gene expression signatures were calculated. Data analyses were performed from June 1, 2020, to January 1, 2023.

Main Outcomes and Measures

The association of clinical variables and gene expression biomarkers with pCR and EFS were studied by logistic regression and Cox analyses.

Results

In the pooled analysis, of 758 women, median age was 49 years, 12% were Asian, 6% Black, and 75% were White. Overall, pCR results were associated with EFS in the ERBB2-enriched (hazard ratio [HR], 0.45; 95% CI, 0.29-0.70; P < .001) and basal-like (HR, 0.19; 95% CI, 0.04-0.86; P = .03) subtypes but not in luminal A or B tumors. Dual trastuzumab plus lapatinib blockade over trastuzumab alone had a trend toward EFS benefit in the intention-to-treat population; however, in the ERBB2-enriched subtype there was a significant and independent EFS benefit of trastuzumab plus lapatinib vs trastuzumab alone (HR, 0.47; 95% CI, 0.27-0.83; P = .009). Overall, 275 of 618 gene expression signatures (44.5%) were significantly associated with pCR and 9 of 618 (1.5%) with EFS. The ERBB2/HER2 amplicon and multiple immune signatures were significantly associated with pCR. Luminal-related signatures were associated with lower pCR rates but better EFS, especially among patients with residual disease and independent of hormone receptor status. There was significant adjusted HR for pCR ranging from 0.45 to 0.81 (higher pCR) and 1.21-1.94 (lower pCR rate); significant adjusted HR for EFS ranged from 0.71 to 0.94.

Conclusions and relevance

In patients with ERBB2/HER2-positive EBC, the association between pCR and EFS differed by tumor intrinsic subtype, and the benefit of dual ERBB2/HER2 blockade was limited to ERBB2-enriched tumors. Immune-activated signatures were concordantly associated with higher pCR rates and better EFS, whereas luminal signatures were associated with lower pCR rates.

Diffsig: Associating Risk Factors With Mutational Signatures

BACKGROUND

Somatic mutational signatures elucidate molecular vulnerabilities to therapy and therefore detecting signatures and classifying tumors with respect to signatures has clinical value. However, identifying the etiology of the mutational signatures remains a statistical challenge, with both small sample sizes and high variability in classification algorithms posing barriers. As a result, few signatures have been strongly linked to particular risk factors.

METHODS

Here we develop a statistical model, Diffsig, for estimating the association of one or more continuous or categorical risk factors with DNA mutational signatures. Diffsig takes into account the uncertainty associated with assigning signatures to samples as well as multiple risk factors' simultaneous effect on observed DNA mutations.

RESULTS

We applied Diffsig to breast cancer data to assess relationships between five established breast-relevant mutational signatures and etiologic variables, confirming known mechanisms of cancer development. In simulation, our model was capable of accurately estimating expected associations in a variety of contexts.

CONCLUSIONS

Diffsig allows researchers to quantify and perform inference on the associations of risk factors with mutational signatures.

IMPACT

We expect Diffsig to provide more robust associations of risk factors with signatures to lead to better understanding of the tumor development process and improved models of tumorigenesis.

PAIRWISE NONLINEAR DEPENDENCE ANALYSIS OF GENOMIC DATA

In The Cancer Genome Atlas (TCGA) data set, there are many interesting nonlinear dependencies between pairs of genes that reveal important relationships and subtypes of cancer. Such genomic data analysis requires a rapid, powerful and interpretable detection process, especially in a high-dimensional environment. We study the nonlinear patterns among the expression of pairs of genes from TCGA using a powerful tool called Binary Expansion Testing. We find many nonlinear patterns, some of which are driven by known cancer subtypes, some of which are novel.

Association of PIK3CA Mutation With Pathologic Complete Response and Outcome by Hormone Receptor Status and Intrinsic Subtype in Early-Stage ERBB2/HER2-Positive Breast Cancer

Importance

PIK3CA mutations may be associated with outcomes of patients with ERBB2/HER2-positive early breast cancer (EBC).

Objectives

To assess if PIK3CA mutations among patients with ERBB2/HER2-positive EBC are associated with treatment response and outcome, and if these associations vary by hormone receptor (HR) status or intrinsic molecular subtype (IMS).

Design, Setting, and Participants

This cohort study derived data on 184 patients from the phase 3 neoadjuvant Cancer and Leukemia Group B (CALGB) 40601 trial that enrolled patients with ERBB2/HER2-positive EBC in North America between January 1, 2008, and December 31, 2012. Participants received neoadjuvant paclitaxel with trastuzumab, lapatinib, or both. Statistical analysis was performed from March 23, 2022, to March 9, 2023.

Exposures

Gene expression profiling by RNA sequencing with Prediction Analysis of Microarray 50-determined IMS and PIK3CA mutations from whole-exome sequencing were obtained from pretreatment biopsies from 184 of 305 trial participants.

Main Outcomes and Measures

The primary end point was pathologic complete response (pCR) and the secondary end point of event-free survival (EFS). The association of PIK3CA mutations with pCR and EFS by HR status and IMS was estimated using logistic and Cox proportional hazards regression models.

Results

All 184 participants were women, with a median age of 49 years (range 24-75 years). A total of 121 participants (66%) had clinical stage II tumors; 32 (17%) had PIK3CA mutations, most frequently H1047R (38% [12 of 32]) and E545K (22% [7 of 32]). PIK3CA mutations were present in 20 of 102 cases of HR-positive EBC (20%) and 12 of 82 cases HR-negative EBC (15%) and varied by IMS (luminal B, 9 of 25 [36%]; luminal A, 2 of 21 [10%]; and ERBB2/HER2-enriched tumors, 19 of 102 [19%]). Pathologic complete response rates were lower in PIK3CA mutated than PIK3CA wild type in the overall population (34% [11 of 32] vs 49% [74 of 152]; P = .14) and were significantly different among those receiving trastuzumab (30% [7 of 23] vs 54% [63 of 117]; P = .045). At a median follow-up of 9 years, PIK3CA mutations were significantly associated with worse EFS in the overall cohort (hazard ratio, 2.58 [95% CI, 1.24-5.35]; P = .01), which persisted in a multivariable model including pCR, HR status, stage, and IMS (hazard ratio, 2.52 [95% CI, 1.16-5.47]; P = .02). The negative association of PIK3CA mutation was significant in HR-positive (hazard ratio, 3.60 [95% CI, 1.45-8.96]; P = .006) and luminal subtypes (hazard ratio, 4.84 [95% CI, 1.08-21.70]; P = .04), but not in nonluminal and HR-negative tumors.

Conclusions and Relevance

In ERBB2/HER2-positive EBC, PIK3CA mutations were associated with lower pCR rates and independently associated with worse long-term EFS. These findings appear to be associated with PIK3CA mutations in HR-positive and luminal EBC.

Expanded detection of BAP1 alterations in cancer and tumor type-specific expression score comparison

BAP1 is a tumor suppressor gene that was originally studied in uveal melanoma (UVM), kidney renal cell clear cell carcinoma (KIRC), and malignant mesothelioma (MESO). Early analyses focused on single-nucleotide variants, but other alteration types such as larger indels and gene-level copy number (CN) loss can also lead to loss of BAP1 expression. We performed integrated multi-omic analyses using data from The Cancer Genome Atlas (TCGA) for 33 cancer types and more than 10,000 individuals. We combined and manually reviewed existing variant calls and new calls derived from a de novo local realignment pipeline across multiple independent variant callers including indel callers, increasing detection of high-quality somatic variant calls by 30% from 91 to 130, including 7 indels ≥40bp. Including CN loss alterations, 1561 samples from 32 cancer types were BAP1-altered, with alterations being predominantly CN-driven. Differential expression and survival analyses revealed both shared and tissue-specific consequences associated with BAP1 alteration. Our findings broadly emphasize the improvements that are gained by using new computational approaches in large cancer-genome studies such as TCGA.

Predicting early breast cancer recurrence from histopathological images in the Carolina Breast Cancer Study

Approaches for rapidly identifying patients at high risk of early breast cancer recurrence are needed. Image-based methods for prescreening hematoxylin and eosin (H&E) stained tumor slides could offer temporal and financial efficiency. We evaluated a data set of 704 1-mm tumor core H&E images (2-4 cores per case), corresponding to 202 participants (101 who recurred; 101 non-recurrent matched on age and follow-up time) from breast cancers diagnosed between 2008-2012 in the Carolina Breast Cancer Study. We leveraged deep learning to extract image information and trained a model to identify recurrence. Cross-validation accuracy for predicting recurrence was 62.4% [95% CI: 55.7, 69.1], similar to grade (65.8% [95% CI: 59.3, 72.3]) and ER status (66.3% [95% CI: 59.8, 72.8]). Interestingly, 70% (19/27) of early-recurrent low-intermediate grade tumors were identified by our image model. Relative to existing markers, image-based analyses provide complementary information for predicting early recurrence.

Immunological and clinicopathological features predict HER2-positive breast cancer prognosis in the neoadjuvant NeoALTTO and CALGB 40601 randomized trials

The identification of prognostic markers in patients receiving neoadjuvant therapy is crucial for treatment optimization in HER2-positive breast cancer, with the immune microenvironment being a key factor. Here, we investigate the complexity of B and T cell receptor (BCR and TCR) repertoires in the context of two phase III trials, NeoALTTO and CALGB 40601, evaluating neoadjuvant paclitaxel with trastuzumab and/or lapatinib in women with HER2-positive breast cancer. BCR features, particularly the number of reads and clones, evenness and Gini index, are heterogeneous according to hormone receptor status and PAM50 subtypes. Moreover, BCR measures describing clonal expansion, namely evenness and Gini index, are independent prognostic factors. We present a model developed in NeoALTTO and validated in CALGB 40601 that can predict event-free survival (EFS) by integrating hormone receptor and clinical nodal status, breast pathological complete response (pCR), stromal tumor-infiltrating lymphocyte levels (%) and BCR repertoire evenness. A prognostic score derived from the model and including those variables, HER2-EveNT, allows the identification of patients with 5-year EFS > 90%, and, in those not achieving pCR, of a subgroup of immune-enriched tumors with an excellent outcome despite residual disease.

Integrated Multimodal Analyses of DNA Damage Response and Immune Markers as Predictors of Response in Metastatic Triple-Negative Breast Cancer in the TNT Trial (NCT00532727)

PURPOSE

The TNT trial (NCT00532727) showed no evidence of carboplatin superiority over docetaxel in metastatic triple-negative breast cancer (mTNBC), but carboplatin benefit was observed in the germline BRCA1/2 mutation subgroup. Broader response-predictive biomarkers are needed. We explored the predictive ability of DNA damage response (DDR) and immune markers.

EXPERIMENTAL DESIGN

Tumor-infiltrating lymphocytes were evaluated for 222 of 376 patients. Primary tumors (PT) from 186 TNT participants (13 matched recurrences) were profiled using total RNA sequencing. Four transcriptional DDR-related and 25 immune-related signatures were evaluated. We assessed their association with objective response rate (ORR) and progression-free survival (PFS). Conditional inference forest clustering was applied to integrate multimodal data. The biology of subgroups was characterized by 693 gene expression modules and other markers.

RESULTS

Transcriptional DDR-related biomarkers were not predictive of ORR to either treatment overall. Changes from PT to recurrence were demonstrated; in chemotherapy-naïve patients, transcriptional DDR markers separated carboplatin responders from nonresponders (P values = 0.017; 0.046). High immune infiltration was associated with docetaxel ORR (interaction P values < 0.05). Six subgroups were identified; the immune-enriched cluster had preferential docetaxel response [62.5% (D) vs. 29.4% (C); P = 0.016]. The immune-depleted cluster had preferential carboplatin response [8.0% (D) vs. 40.0% (C); P = 0.011]. DDR-related subgroups were too small to assess ORR.

CONCLUSIONS

High immune features predict docetaxel response, and high DDR signature scores predict carboplatin response in treatment-naïve mTNBC. Integrating multimodal DDR and immune-related markers identifies subgroups with differential treatment sensitivity. Treatment options for patients with immune-low and DDR-proficient tumors remains an outstanding need. Caution is needed using PT-derived transcriptional signatures to direct treatment in mTNBC, particularly DDR-related markers following prior chemotherapy.

Prognostic and Predictive Value of Immune-Related Gene Expression Signatures vs Tumor-Infiltrating Lymphocytes in Early-Stage ERBB2/HER2-Positive Breast Cancer: A Correlative Analysis of the CALGB 40601 and PAMELA Trials

Importance

Both tumor-infiltrating lymphocytes (TILs) assessment and immune-related gene expression signatures by RNA profiling predict higher pathologic complete response (pCR) and improved event-free survival (EFS) in patients with early-stage ERBB2/HER2-positive breast cancer. However, whether these 2 measures of immune activation provide similar or additive prognostic value is not known.

Objective

To examine the prognostic ability of TILs and immune-related gene expression signatures, alone and in combination, to predict pCR and EFS in patients with early-stage ERBB2/HER2-positive breast cancer treated in 2 clinical trials.

Design, Setting, and Participants

In this prognostic study, a correlative analysis was performed on the Cancer and Leukemia Group B (CALGB) 40601 trial and the PAMELA trial. In the CALGB 40601 trial, 305 patients were randomly assigned to weekly paclitaxel with trastuzumab, lapatinib, or both for 16 weeks. The primary end point was pCR, with a secondary end point of EFS. In the PAMELA trial, 151 patients received neoadjuvant treatment with trastuzumab and lapatinib for 18 weeks. The primary end point was the ability of the HER2-enriched subtype to predict pCR. The studies were conducted from October 2013 to November 2015 (PAMELA) and from December 2008 to February 2012 (CALGB 40601). Data analyses were performed from June 1, 2020, to January 1, 2022.

Main Outcomes and Measures

Immune-related gene expression profiling by RNA sequencing and TILs were assessed on 230 CALGB 40601 trial pretreatment tumors and 138 PAMELA trial pretreatment tumors. The association of these biomarkers with pCR (CALGB 40601 and PAMELA) and EFS (CALGB 40601) was studied by logistic regression and Cox analyses.

Results

The median age of the patients was 50 years (IQR, 42-50 years), and 305 (100%) were women. Of 202 immune signatures tested, 166 (82.2%) were significantly correlated with TILs. In both trials combined, TILs were significantly associated with pCR (odds ratio, 1.01; 95% CI, 1.01-1.02; P = .02). In addition to TILs, 36 immune signatures were significantly associated with higher pCR rates. Seven of these signatures outperformed TILs for predicting pCR, 6 of which were B-cell related. In a multivariable Cox model adjusted for clinicopathologic factors, including PAM50 intrinsic tumor subtype, the immunoglobulin G signature, but not TILs, was independently associated with EFS (immunoglobulin G signature-adjusted hazard ratio, 0.63; 95% CI, 0.42-0.93; P = .02; TIL-adjusted hazard ratio, 1.00; 95% CI, 0.98-1.02; P = .99).

Conclusions and Relevance

Results of this study suggest that multiple B-cell-related signatures were more strongly associated with pCR and EFS than TILs, which largely represent T cells. When both TILs and gene expression are available, the prognostic value of immune-related signatures appears to be superior.

Abstract PD18-04: Prognostic implications of PIK3CA mutation by hormone receptor status and intrinsic subtype in early stage HER2-positive breast cancer: a correlative analysis from CALGB 40601

Background PIK3CA mutations have been described in 20-25% of early-stage HER2-positive breast tumors [1], and are associated with reduced pathologic complete response (pCR) rate after chemotherapy and anti-HER2 agents [2]. However, the independence of this finding and association with long-term outcomes within HER2+ patients is still largely unknown. Here, we studied the prognostic implications of PIK3CA mutations by hormone receptor (HR) status and intrinsic subtype in patients with early stage HER2+ breast cancer enrolled in CALGB 40601. Method In CALGB 40601, gene expression profiling by RNA sequencing (RNAseq) with PAM50-determined intrinsic subtype and PIK3CA mutations from whole exome sequencing (WES) were obtained from 184/305 (60%) pretreatment core biopsies. We examined the association of PIK3CA mutations with pCR and event free survival (EFS) by HR status and intrinsic subtype using logistic and Cox regression analyses. Results PIK3CA mutations were found in 32 patients (32/184, 17%). The most frequent mutation was H1047R (12/32,38%), followed by E545K (7/32,22%) and E542K (5/32,16%). PIK3CA mutations were present in 20% and 15% of HR-positive and HR-negative BC subpopulations, respectively. Within Luminal-B, Luminal-A and HER2-Enriched breast tumors, PIK3CA mutations occurred in 36%, 10% and 19% respectively. In the overall population there was lower rate of pCR in mutated-PIK3CA patients than wild-type (34% vs 49%). Using only the subset of patients treated with neoadjuvant trastuzumab-based therapy as standard of care (excluding the lapatinib plus paclitaxel arm), we found a statistically significant lower pCR rate among PIK3CA-mutated tumors using logistic regression model (30% vs 54%, OR=0.30, p=0.045). At a median follow-up of 9.1 years, the presence of PIK3CA mutation was significantly associated with worse EFS in the overall study population (HR 2.58, 95% CI 1.24- 5.35, p=0.011). In a multivariable model including pCR status, HR status and intrinsic subtype (HER2-E vs. not), PIK3CA mutation was independently and significantly associated with worse EFS (HR 2.18, 95% CI 1.04- 4.56, p=0.039). The negative impact of PIK3CA mutation on EFS was statistically significant only in patients with HR-positive (HR 3.6, 95% CI 1.45-8.96, p=0.06) and luminal breast tumors (HR 4.84, 95% CI 1.08-21.7, p=0.039), but not in HR-negative and non-luminal subtypes. Conclusion In our study, the presence of PIK3CA mutation was significantly associated with lower pCR rates in patients treated with chemotherapy plus trastuzumab. Moreover, in uni- and multivariable Cox models, PIK3CA mutations were associated with worse long-term survival, which appeared to be driven by HR-positive and luminal HER2-positive breast tumors. References 1. Cancer Genome Atlas Network. Comprehensive molecular portraits of human breast tumors. Nature 2012;490:61–70. 2. Loibl S, Majewski I, Guarneri V, Nekljudova V, Holmes E, Bria E, et al PIK3CA mutations are associated with reduced pathological complete response rates in primary HER2-positive breast cancer: pooled analysis of 967 patients from five prospective trials investigating lapatinib and trastuzumab. Ann Oncol 2016;27:1519–25.

Citation Format: Paola Zagami, Aranzazu Fernandez-Martinez, Naim U. Rashid, Katherine A Hoadley, Patty Spears, Charles M. Perou, Lisa Carey. Prognostic implications of PIK3CA mutation by hormone receptor status and intrinsic subtype in early stage HER2-positive breast cancer: a correlative analysis from CALGB 40601. [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 PD18-04.

Abstract PD9-06: Histopathological and molecular immune landscape and DNA damage response signatures to predict response to carboplatin and docetaxel in TNT trial TNBC cohort

Background The TNT trial (NCT00532727) showed no evidence of carboplatin (C) superiority over docetaxel (D) overall in metastatic triple negative breast cancers (TNBC), but a C benefit was observed in the pre-specified sub-group analysis in patients with a gBRCA1/2 mutation (Tutt et al, Nat Med 2018). Given only ~30% of patients have a gBRCA1/2 mutation, broader predictive biomarkers of response are needed. In this cohort we previously found that DNA Damage Response (DDR) signatures were associated with improved C response in chemotherapy (CT) naïve patients only (Tovey et al, ASCO 2020). Since DDR activities influence tumour immune-microenvironment, we explored the predictive ability of immune cell markers and performed integrative analyses on multi-omics features to identify novel TNBC subgroups. Patients and Methods Tumour infiltrating lymphocytes (TILs) were evaluated on haematoxylin and eosin stained primary tumour (PT) slides for 222/376 TNT patients. Formalin-fixed paraffin-embedded PT tissues from 186/376 TNT patients were successfully profiled using total RNA-sequencing. Matched recurrence (REC) was also sequenced for 13 patients. Twenty-five immune signatures were assessed. Logistic regression and restricted mean progression free survival (PFS) were applied to delineate the relationship of these features with treatment outcomes. Random forest clustering of multi-omics DDR and immune biology markers, including gene expression signatures and mutation/methylation status, was applied to identify subgroups. We further molecularly characterised these clusters through supervised clustering of 693 gene expression “modules” (sets of co-expressed genes), immune cell deconvolution and genomic scars. Results Immune gene expression signatures and TILs were highly correlated. Average immune infiltration based on ConsensusTME was lower in mutated/methylated tumours compared with BRCA1 wildtype tumours (p=0.04). Immune signature score markers decreased from PT to REC, demonstrating a dynamic immune microenvironment. In the overall population and when restricting to prior CT treated patients, high immune infiltration (gene expression based & TILs) was associated with response to D while C response rates were not associated with immune scores (interaction p-values&lt; 0.05). This did not translate to a PFS benefit. Multi-omics clustering identified 6 biological subgroups including immune enriched, immune depleted, DDR deficient and proficient clusters as well as 2 small clusters with no obvious distinguishing features. Immune enriched TNBC were predominantly basal-like immune activated with high B-cell/T-cell diversity. Immune depleted TNBC showed higher activity of proliferation and DDR pathway modules. DDR proficient tumours had low expression of immune markers and enrichment for ESR1/PGR expression, markers of extra cellular formation, cell structure, lipid metabolism and proliferation. The DDR deficient cluster was enriched for proliferation and demonstrated high number of TILs despite no apparent enrichment for gene expression-based immune modules. In the prior CT treated cohort, the immune enriched cluster had preferential response to D (62.5% (D) vs. 29.4% (C); p=0.02). The immune depleted cluster had preferential response to C (8.0% (D) vs. 40.0% (C); p=0.01). Numbers were too small to assess differential response within the other clusters or in the CT naïve cohort. Conclusions Tumours with high immune features have high response to D while those with low immune features have preferential response to C in advanced TNBC. Combining multi-omics markers of DDR deficiency and immune biology can identify clusters of patients with distinct biological profiles and differential treatment specific response rates.

Citation Format: Holly Tovey, Orsolya Sipos, Katherine A Hoadley, Joel S Parker, Jelmar Quist, Sarah Kernaghan, Lucy Kilburn, Roberto Salgado, Sherene Loi, Richard D Kennedy, Ioannis Roxanis, Patrycja Gazinska, Sarah E. Pinder, Judith Bliss, Charles M. Perou, Syed Haider, Andrew Tutt, Anita Grigoriadis, Maggie Chon U Cheang. Histopathological and molecular immune landscape and DNA damage response signatures to predict response to carboplatin and docetaxel in TNT trial TNBC cohort [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 PD9-06.

Abstract P2-03-08: Deconstructing the molecular characteristics of ER+ HER2+ early breast cancer in the POETIC trial using multiplex immunofluorescence and gene expression profiles

Background: POETIC was a phase III clinical trial, with patients randomised 2:1 to 2-week perioperative aromatase inhibitor (POAI) vs control for postmenopausal women with oestrogen receptor positive (ER+) early breast cancer (BC) (Smith et al., Lancet Oncology 2020). Our previous study on POETIC trial patients with ER+ human epidermal growth factor receptor 2 positive (HER2+) BC suggested both HER2 enriched subtype (HER2-E) and immune enrichment pre-POAI (baseline, B) are main drivers of poor early response to POAI (Bergamino et al., 2022). However, some patients with HER2-E or immune enriched BC at B still showed good response to POAI. In this study, we aim to further investigate a sub-cohort of ER+ HER2+ BC from the POETIC trial, including a subset of aforementioned HER2-E tumours, to further explore the multi-modal molecular characteristics of the tumours resistant to POAI.

Methods: Proliferation rate was assessed as percentage of cancer cells stained by Ki67. Patient POAI response was determined by Ki67 reduction at 2 weeks of treatment. A sub-cohort of 37 patients were selected based on response and classified as poor responders (PR, reduction &lt; 30%, n=18), good responders (GR, reduction &gt; 90%, n=11) and good responders with HER2-E BC at B (GR, reduction &gt; 65%, n=8). Paired B and post-POAI (surgery, S) samples were taken from each patient of the sub-cohort. Multiplex immunofluorescence (mIF) was performed on these samples, measuring the immune cell densities in stroma and tumour compartments using five biomarkers: CD3 (all T cells), CD20 (B cells), CD68 (Macrophages), FOXP3 (regulatory T cells), and CD3 FOXP3 co-expression. The samples were also profiled using Breast Cancer 360TM (NanoString, BC360), covering the expressions of 758 genes and 46 biological signatures. Wilcoxon test, hierarchical clustering and spearman correlation test were performed to compare the tumour characteristics of GR and PR.

Results: In this study, two B and four S samples were not achievable for mIF experiments due to low tumour content. At B (n = 35), among the five mIF biomarker measurements in stroma and tumour, only the stromal CD3 density was significantly different between GR (median = 0.0013) and PR (median = 0.0003, p = 0.041). In GR, HER2-E BC at B were separated into immune-high and immune-low groups with mIF biomarkers at B; the immune-high group was more likely to change into luminal subtypes post-POAI, while the immune-low group remained HER2-E. After POAI, the density changes in five mIF biomarkers in stroma and CD68 in tumour were all significantly higher in PR than GR (Table 1, n of paired samples = 62). The BC360 signatures of BC p53 (p &lt; 0.001), BC proliferation (p &lt; 0.001), LumB (p &lt; 0.001) and HER2-E correlation coefficients (p &lt; 0.001) were significantly downregulated in GR after POAI, while LumA correlation coefficients (p &lt; 0.001) were notably increased.

Conclusions: Our results suggest that for this sub-cohort, increased stromal immune response is associated with poor response to 2-week POAI in ER+ HER2+ early BC. HER2-E GR display visible immune heterogeneity at B. Lower-risk BC characteristics were exhibited in GR after the 2-week treatment. Further integrating mIF imaging data and additional digital spatial profiling are ongoing to reveal additional characteristics of ER+ HER2+ BC and tumour microenvironment predicting POAI resistance.

Table 1: List of medians of log2 fold changes in mIF biomarker densities between GR and PR among the 62 paired samples, and Wilcoxon test p-values.

Citation Format: Xixuan Zhu, Hui Xiao, Elena López-Knowles, Milana A. Bergamino Sirvén, Anastasia Alataki, Perry Maxwell, Holly Tovey, Lucy Kilburn, Chris Holcombe, Anthony Skene, Ian Smith, John Robertson, Katherine A Hoadley, Roberto Salgado, Judith Bliss, Nicholas Turner, Manuel Salto-Tellez, Gene Schuster, Mitch Dowsett, Maggie Chon U Cheang. Deconstructing the molecular characteristics of ER+ HER2+ early breast cancer in the POETIC trial using multiplex immunofluorescence and gene expression profiles [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 P2-03-08.

Diffsig: Associating Risk Factors With Mutational Signatures

Somatic mutational signatures elucidate molecular vulnerabilities to therapy and therefore detecting signatures and classifying tumors with respect to signatures has clinical value. However, identifying the etiology of the mutational signatures remains a statistical challenge, with both small sample sizes and high variability in classification algorithms posing barriers. As a result, few signatures have been strongly linked to particular risk factors. Here we present Diffsig, a model and R package for estimating the association of risk factors with mutational signatures, suggesting etiologies for the pre-defined mutational signatures. Diffsig is a Bayesian Dirichlet-multinomial hierarchical model that allows testing of any type of risk factor while taking into account the uncertainty associated with samples with a low number of observations. In simulation, we found that our method can accurately estimate risk factor-mutational signal associations. We applied Diffsig to breast cancer data to assess relationships between five established breast-relevant mutational signatures and etiologic variables, confirming known mechanisms of cancer development. Diffsig is implemented as an R package available at: https://github.com/jennprk/diffsig.

Landscape of Genetic Alterations Underlying Hallmark Signature Changes in Cancer Reveals TP53 Aneuploidy-driven Metabolic Reprogramming

The hallmark signatures based on gene expression capture core cancer processes. Through a pan-cancer analysis, we describe the overview of hallmark signatures across tumor types/subtypes and reveal significant relationships between these signatures and genetic alterations. TP53 mutation exerts diverse changes, including increased proliferation and glycolysis, which are closely mimicked by widespread copy-number alterations. Hallmark signature and copy-number clustering identify a cluster of squamous tumors and basal-like breast and bladder cancers with elevated proliferation signatures, frequent TP53 mutation, and high aneuploidy. In these basal-like/squamous TP53-mutated tumors, a specific and consistent spectrum of copy-number alterations is preferentially selected prior to whole-genome duplication. Within Trp53-null breast cancer mouse models, these copy-number alterations spontaneously occur and recapitulate the hallmark signature changes observed in the human condition. Together, our analysis reveals intertumor and intratumor heterogeneity of the hallmark signatures, uncovering an oncogenic program induced by TP53 mutation and select aneuploidy events to drive a worsened prognosis.

Significance

Our data demonstrate that TP53 mutation and a resultant selected pattern of aneuploidies cause an aggressive transcriptional program including upregulation of glycolysis signature with prognostic implications. Importantly, basal-like breast cancer demonstrates genetic and/or phenotypic changes closely related to squamous tumors including 5q deletion that reveal alterations that could offer therapeutic options across tumor types regardless of tissue of origin.

Incorporating RNA-based Risk Scores for Genomic Instability to Predict Breast Cancer Recurrence and Immunogenicity in a Diverse Population

Markers of genomic instability, including TP53 status and homologous recombination deficiency (HRD), are candidate biomarkers of immunogenicity and immune-mediated survival, but little is known about the distribution of these markers in large, population-based cohorts of racially diverse patients with breast cancer. In prior clinical trials, DNA-based approaches have been emphasized, but recent data suggest that RNA-based assessment can capture pathway differences conveniently and may be streamlined with other RNA-based genomic risk scores. Thus, we used RNA expression to study genomic instability (HRD and TP53 pathways) in context of the breast cancer immune microenvironment in three datasets (total n = 4,892), including 1,942 samples from the Carolina Breast Cancer Study, a population-based study that oversampled Black (n = 1,026) and younger women (n = 1,032). Across all studies, 36.9% of estrogen receptor (ER)-positive and 92.6% of ER-negative breast cancer had presence of at least one genomic instability signature. TP53 and HRD status were significantly associated with immune expression in both ER-positive and ER-negative breast cancer. RNA-based genomic instability signatures were associated with higher PD-L1, CD8 T-cell marker, and global and multimarker immune cell expression. Among tumors with genomic instability signatures, adaptive immune response was associated with improved recurrence-free survival regardless of ER status, highlighting genomic instability as a candidate marker for predicting immunotherapy response. Leveraging a convenient, integrated RNA-based approach, this analysis shows that genomic instability interacts with immune response, an important target in breast cancer overall and in Black women who experience higher frequency of TP53 and HR deficiency.

Significance

Despite promising advances in breast cancer immunotherapy, predictive biomarkers that are valid across diverse populations and breast cancer subtypes are needed. Genomic instability signatures can be coordinated with other RNA-based scores to define immunogenic breast cancers and may have value in stratifying immunotherapy trial participants.

Multiomics in primary and metastatic breast tumors from the AURORA US network finds microenvironment and epigenetic drivers of metastasis

The AURORA US Metastasis Project was established with the goal to identify molecular features associated with metastasis. We assayed 55 females with metastatic breast cancer (51 primary cancers and 102 metastases) by RNA sequencing, tumor/germline DNA exome and low-pass whole-genome sequencing and global DNA methylation microarrays. Expression subtype changes were observed in ~30% of samples and were coincident with DNA clonality shifts, especially involving HER2. Downregulation of estrogen receptor (ER)-mediated cell-cell adhesion genes through DNA methylation mechanisms was observed in metastases. Microenvironment differences varied according to tumor subtype; the ER+/luminal subtype had lower fibroblast and endothelial content, while triple-negative breast cancer/basal metastases showed a decrease in B and T cells. In 17% of metastases, DNA hypermethylation and/or focal deletions were identified near HLA-A and were associated with reduced expression and lower immune cell infiltrates, especially in brain and liver metastases. These findings could have implications for treating individuals with metastatic breast cancer with immune- and HER2-targeting therapies.

RNA-Based Classification of Homologous Recombination Deficiency in Racially Diverse Patients with Breast Cancer

BACKGROUND

Aberrant expression of DNA repair pathways such as homologous recombination (HR) can lead to DNA repair imbalance, genomic instability, and altered chemotherapy response. DNA repair imbalance may predict prognosis, but variation in DNA repair in diverse cohorts of breast cancer patients is understudied.

METHODS

To identify RNA-based patterns of DNA repair expression, we performed unsupervised clustering on 51 DNA repair-related genes in the Cancer Genome Atlas Breast Cancer [TCGA BRCA (n = 1,094)] and Carolina Breast Cancer Study [CBCS (n = 1,461)]. Using published DNA-based HR deficiency (HRD) scores (high-HRD ≥ 42) from TCGA, we trained an RNA-based supervised classifier. Unsupervised and supervised HRD classifiers were evaluated in association with demographics, tumor characteristics, and clinical outcomes.

RESULTS

: Unsupervised clustering on DNA repair genes identified four clusters of breast tumors, with one group having high expression of HR genes. Approximately 39.7% of CBCS and 29.3% of TCGA breast tumors had this unsupervised high-HRD (U-HRD) profile. A supervised HRD classifier (S-HRD) trained on TCGA had 84% sensitivity and 73% specificity to detect HRD-high samples. Both U-HRD and S-HRD tumors in CBCS had higher frequency of TP53 mutant-like status (45% and 41% enrichment) and basal-like subtype (63% and 58% enrichment). S-HRD high was more common among black patients. Among chemotherapy-treated participants, recurrence was associated with S-HRD high (HR: 2.38, 95% confidence interval = 1.50-3.78).

CONCLUSIONS

HRD is associated with poor prognosis and enriched in the tumors of black women.

IMPACT

RNA-level indicators of HRD are predictive of breast cancer outcomes in diverse populations.

Collaborative study from the Bladder Cancer Advocacy Network for the genomic analysis of metastatic urothelial cancer

Urothelial Cancer - Genomic Analysis to Improve Patient Outcomes and Research (NCT02643043), UC-GENOME, is a genomic analysis and biospecimen repository study in 218 patients with metastatic urothelial carcinoma. Here we report on the primary outcome of the UC-GENOME-the proportion of subjects who received next generation sequencing (NGS) with treatment options-and present the initial genomic analyses and clinical correlates. 69.3% of subjects had potential treatment options, however only 5.0% received therapy based on NGS. We found an increased frequency of TP53E285K mutations as compared to non-metastatic cohorts and identified features associated with benefit to chemotherapy and immune checkpoint inhibition, including: Ba/Sq and Stroma-rich subtypes, APOBEC mutational signature (SBS13), and inflamed tumor immune phenotype. Finally, we derive a computational model incorporating both genomic and clinical features predictive of immune checkpoint inhibitor response. Future work will utilize the biospecimens alongside these foundational analyses toward a better understanding of urothelial carcinoma biology.

Race and Ancestry in Immune Response to Breast Cancer

Martini and colleagues performed genetic ancestry estimation on a unique international triple-negative breast cancer (TNBC) study enriched for participants with African ancestry. They identified gene signatures indicative of ancestry in race-associated TNBC and found ancestry-associated immunologic differences that may contribute to racial disparities in breast cancer. See related article by Martini et al., p. 2530 (5).

Analysis of germline-driven ancestry-associated gene expression in cancers

Differential mRNA expression between ancestry groups can be explained by both genetic and environmental factors. We outline a computational workflow to determine the extent to which germline genetic variation explains cancer-specific molecular differences across ancestry groups. Using multi-omics datasets from The Cancer Genome Atlas (TCGA), we enumerate ancestry-informative markers colocalized with cancer-type-specific expression quantitative trait loci (e-QTLs) at ancestry-associated genes. This approach is generalizable to other settings with paired germline genotyping and mRNA expression data for a multi-ethnic cohort.

For complete details on the use and execution of this protocol, please refer to Carrot-Zhang et al. (2020), Robertson et al. (2021), and Sayaman et al. (2021).

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Protocol for obtaining controlled access TCGA datasets

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Protocols for quality control analysis and genotype imputation of TCGA germline data

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Statistical analysis for determining ancestry-associated SNPs

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Determination of ancestry-associated germline genetic variation driving mRNA expression

Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

DNA Damage Repair Classifier Defines Distinct Groups in Hepatocellular Carcinoma

Simple Summary

DNA repair pathways have been implicated in hepatocellular carcinoma outcomes. We found that hepatocellular carcinomas (HCC) could be separated into two groups (high and low) based on the overall expression of genes involved in DNA repair. Among the low repair group, there were three subgroups, one of which shared features of the high repair group. Given the important role of liver in metabolism and detoxification and its regenerative capacity, proliferation and DNA damage responses are critical in subdividing major biological categories of liver tumors. High repair samples showed more proliferative and regenerative signatures and had poorer outcomes versus the low repair that were more associated with the genes involved in normal liver biology. These biological groups suggest that dysregulation in endogenous liver processes promotes a pro-tumorigenic microenvironment that may facilitate tumor progression or identify tumors that require more substantial clinical intervention.

Abstract

DNA repair pathways have been associated with variability in hepatocellular carcinoma (HCC) clinical outcomes, but the mechanism through which DNA repair varies as a function of liver regeneration and other HCC characteristics is poorly understood. We curated a panel of 199 genes representing 15 DNA repair pathways to identify DNA repair expression classes and evaluate their associations with liver features and clinicopathologic variables in The Cancer Genome Atlas (TCGA) HCC study. We identified two groups in HCC, defined by low or high expression across all DNA repair pathways. The low-repair group had lower grade and retained the expression of classical liver markers, whereas the high-repair group had more clinically aggressive features, increased p53 mutant-like gene expression, and high liver regenerative gene expression. These pronounced features overshadowed the variation in the low-repair subset, but when considered separately, the low-repair samples included three subgroups: L1, L2, and L3. L3 had high DNA repair expression with worse progression-free (HR 1.24, 95% CI 0.81–1.91) and overall (HR 1.63, 95% CI 0.98–2.71) survival. High-repair outcomes were also significantly worse compared with the L1 and L2 groups. HCCs vary in DNA repair expression, and a subset of tumors with high regeneration profoundly disrupts liver biology and poor prognosis.

The Landscape of Immune Microenvironments in Racially Diverse Breast Cancer Patients

BACKGROUND

Immunotherapy is a rapidly evolving treatment option in breast cancer; However, the breast cancer immune microenvironment is understudied in Black and younger (<50 years) patients.

METHODS

We used histologic and RNA-based immunoprofiling methods to characterize the breast cancer immune landscape in 1,952 tumors from the Carolina Breast Cancer Study (CBCS), a population-based study that oversampled Black (n = 1,030) and young women (n = 1,039). We evaluated immune response leveraging markers for 10 immune cell populations, compared profiles to those in The Cancer Genome Atlas (TCGA) Project [n = 1,095 tumors, Black (n = 183), and young women (n = 295)], and evaluated in association with clinical and demographic variables, including recurrence.

RESULTS

Consensus clustering identified three immune clusters in CBCS (adaptive-enriched, innate-enriched, or immune-quiet) that varied in frequency by race, age, tumor grade and subtype; however, only two clusters were identified in TCGA, which were predominantly comprised of adaptive-enriched and innate-enriched tumors. In CBCS, the strongest adaptive immune response was observed for basal-like, HER2-positive (HER2+), triple-negative breast cancer (TNBC), and high-grade tumors. Younger patients had higher proportions of adaptive-enriched tumors, particularly among estrogen receptor (ER)-negative (ER-) cases. Black patients had higher frequencies of both adaptive-enriched and innate-enriched tumors. Immune clusters were associated with recurrence among ER- tumors, with adaptive-enriched showing the best and innate-enriched showing the poorest 5-year recurrence-free survival.

CONCLUSIONS

These data suggest that immune microenvironments are intricately related to race, age, tumor subtype, and grade.

IMPACT

Given higher mortality among Black and young women, more defined immune classification using cell-type-specific panels could help explain higher recurrence and ultimately lead to targetable interventions.

Genetic changes associated with relapse in favorable histology Wilms tumor: A Children's Oncology Group AREN03B2 study

Over the last decade, sequencing of primary tumors has clarified the genetic underpinnings of Wilms tumor but has not affected therapy, outcome, or toxicity. We now sharpen our focus on relapse samples from the umbrella AREN03B2 study. We show that over 40% of relapse samples contain mutations in SIX1 or genes of the MYCN network, drivers of progenitor proliferation. Not previously seen in large studies of primary Wilms tumors, DIS3 and TERT are now identified as recurrently mutated. The analysis of primary-relapse tumor pairs suggests that 11p15 loss of heterozygosity (and other copy number changes) and mutations in WT1 and MLLT1 typically occur early, but mutations in SIX1, MYCN, and WTX are late developments in some individuals. Most strikingly, 75% of relapse samples had gain of 1q, providing strong conceptual support for studying circulating tumor DNA in clinical trials to better detect 1q gain earlier and monitor response.

A hierarchical spike-and-slab model for pan-cancer survival using pan-omic data

Background

Pan-omics, pan-cancer analysis has advanced our understanding of the molecular heterogeneity of cancer. However, such analyses have been limited in their ability to use information from multiple sources of data (e.g., omics platforms) and multiple sample sets (e.g., cancer types) to predict clinical outcomes. We address the issue of prediction across multiple high-dimensional sources of data and sample sets by using molecular patterns identified by BIDIFAC+, a method for integrative dimension reduction of bidimensionally-linked matrices, in a Bayesian hierarchical model. Our model performs variable selection through spike-and-slab priors that borrow information across clustered data. We use this model to predict overall patient survival from the Cancer Genome Atlas with data from 29 cancer types and 4 omics sources and use simulations to characterize the performance of the hierarchical spike-and-slab prior.

Results

We found that molecular patterns shared across all or most cancers were largely not predictive of survival. However, our model selected patterns unique to subsets of cancers that differentiate clinical tumor subtypes with markedly different survival outcomes. Some of these subtypes were previously established, such as subtypes of uterine corpus endometrial carcinoma, while others may be novel, such as subtypes within a set of kidney carcinomas. Through simulations, we found that the hierarchical spike-and-slab prior performs best in terms of variable selection accuracy and predictive power when borrowing information is advantageous, but also offers competitive performance when it is not.

Conclusions

We address the issue of prediction across multiple sources of data by using results from BIDIFAC+ in a Bayesian hierarchical model for overall patient survival. By incorporating spike-and-slab priors that borrow information across cancers, we identified molecular patterns that distinguish clinical tumor subtypes within a single cancer and within a group of cancers. We also corroborate the flexibility and performance of using spike-and-slab priors as a Bayesian variable selection approach.

Abstract LB176: Multiplatform analysis of matched primary and metastatic breast tumors from the AURORA US Network identifies microenvironment features as drivers of metastasis

Background: Metastatic breast cancer (MBC) patients often have short survival, and successful treatment represents one of the most challenging aspects of cancer care. This poor prognosis is likely multifactorial, including increased clonal heterogeneity, drug resistance mechanisms, and alterations of the tumor microenvironment.

Methods: The primary data source was multi-platform data coming from the AURORA US Project that includes RNAseq, DNAseq, and DNA methylation arrays, which assayed 55 MBC patients representing 51 primary cancers and 102 linked metastatic specimens. In addition, RNA sequencing data from two other datasets of primary tumor-metastasis pairs were also used (i.e. UNC Tumor Donation Program/RAP dataset (24 primary and 74 metastasis specimens), and the GEICAM/2009-03 ConvertHER trial dataset (102 primaries and 102 metastatic pairs)). In total, this combined RNAseq dataset contained 177 primary tumors and 278 metastases, including 28 liver, 18 lung, 12 brain, and 24 lymph node metastases. We used these data to address two pressing questions, namely: 1) do gene expression features vary in primary tumors vs metastases according to PAM50 expression subtype, and 2) do gene expression features vary according to site of metastasis.

Results: Using the AURORA multi-platform data, we determined that 17% of metastatic tumors (mainly TNBC/Basal-like) showed reduced expression of HLA-A that was associated with DNA methylation and/or focal DNA deletions near the HLA-A locus; these methylated tumors also showed concomitant lower immune cell infiltrates. Reduced expression of HLA-A gene and immune cell infiltrates were also validated at the RNA level in RAP dataset. Next, RNA expression differences were examined using the combined data set and varied according to tumor subtype. ER+/Luminal metastases had lower fibroblast and endothelial cell content, while triple negative (TNBC)/Basal-like metastases showed a dramatic decrease in T cell and B cell signatures/features. Comparative analyses between primary and site-specific metastasis (i.e., primary vs liver metastasis) or between sites of metastases (i.e., liver vs lung metastasis) revealed that both liver and brain, on average, had low immune cell features regardless of the primary tumor phenotype. Even within the same patient, we detected low immune cell features in brain and liver metastases compared to lung and lymph node metastases. Lastly, liver metastases showed a gain of Luminal B/HER2E gene expression features and MYC targets, and brain TNBC metastasis showed a gain of cell differentiation/Luminal-related gene signatures.

Conclusions: These findings could have direct implications for the treatment of MBC patients with immune-based therapies and suggest new therapeutic avenues depending upon the tumor metastasis phenotype, and site of metastasis.

Citation Format: Susana Garcia Recio, Toshinori Hinoue, Gregory L. Wheeler, Benjamin J. Kelly, Justin M. Balko, Katherine A. Hoadley, Peter W. Laird, Elaine R. Mardis, Charles M. Perou. Multiplatform analysis of matched primary and metastatic breast tumors from the AURORA US Network identifies microenvironment features as drivers of metastasis [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 LB176.

Prognostic significance of RNA-based TP53 pathway function among estrogen receptor positive and negative breast cancer cases

TP53 and estrogen receptor (ER) are essential in breast cancer development and progression, but TP53 status (by DNA sequencing or protein expression) has been inconsistently associated with survival. We evaluated whether RNA-based TP53 classifiers are related to survival. Participants included 3213 women in the Carolina Breast Cancer Study (CBCS) with invasive breast cancer (stages I-III). Tumors were classified for TP53 status (mutant-like/wildtype-like) using an RNA signature. We used Cox proportional hazards models to estimate covariate-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for breast cancer-specific survival (BCSS) among ER- and TP53-defined subtypes. RNA-based results were compared to DNA- and IHC-based TP53 classification, as well as Basal-like versus non-Basal-like subtype. Findings from the diverse (50% Black), population-based CBCS were compared to those from the largely white METABRIC study. RNA-based TP53 mutant-like was associated with BCSS among both ER-negatives and ER-positives (HR (95% CI) = 5.38 (1.84-15.78) and 4.66 (1.79-12.15), respectively). Associations were attenuated when using DNA- or IHC-based TP53 classification. In METABRIC, few ER-negative tumors were TP53-wildtype-like, but TP53 status was a strong predictor of BCSS among ER-positives. In both populations, the effect of TP53 mutant-like status was similar to that for Basal-like subtype. RNA-based measures of TP53 status are strongly associated with BCSS and may have value among ER-negative cancers where few prognostic markers have been robustly validated. Given the role of TP53 in chemotherapeutic response, RNA-based TP53 as a prognostic biomarker could address an unmet need in breast cancer.

Prognostic and predictive implications of the intrinsic subtypes and gene expression signatures in early-stage HER2+ breast cancer: A pooled analysis of CALGB 40601, NeoALTTO, and NSABP B-41 trials

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Background: Several biologic features are implicated in the differences in response and survival to dual (trastuzumab and lapatinib [HL]) vs. single (trastuzumab [H]) HER2-blockade across neoadjuvant trials in early-stage HER2+ breast cancer. We evaluated the association of intrinsic subtypes and gene expression signatures with pathologic complete response (pCR) and event-free survival (EFS) in a pooled analysis of three independent phase III neoadjuvant studies with similar designs: CALGB 40601 (Alliance), NeoALTTO, and NSABP B-41. Methods: Gene expression profiling by RNA sequencing was assessed on 761 pre-treatment samples (264 from CALGB 40601, 249 from NeoALTTO, 248 from NSABP B-41). Intrinsic subtypes and 759 gene expression signatures were calculated. We studied the association of pCR and the benefit of dual (HL) vs. single (H) HER2-blockade by tumor intrinsic subtype in the pooled set. The ability of multiple gene expression signatures to predict pCR and EFS across the three studies was also tested by logistic and Cox regression analyses. Results: pCR status was associated with EFS only in HER2-Enriched (HR 0.45, 95% CI 0.29-0.71, p-value < 0.001) and Basal-like (HR 0.19, 95% CI 0.04-0.86, p-value 0.031) intrinsic subtypes, but not in Luminal and/or ER+ tumors. The EFS benefit of dual vs. single HER2-blockade was limited to HER2-Enriched tumors (HR 0.47, 95% CI 0.27-0.81, p-value 0.007). When evaluating the three clinical trials separately, we found 89/759 (11.7%) gene expression signatures in common for the prediction of pCR across the three clinical trials, including HER2-amplicon and immune activation signatures. Luminal-related signatures were associated with lower pCR rates but better EFS outcomes, especially in patients with residual disease. Stratified Cox regression models by study showed a significant and strong association of NK, B and plasma cells, as well as Ig-related signatures with a better EFS outcome, while vascular, proliferation, and metastasis signatures were associated with poor EFS. Conclusions: In early-stage HER2+ breast cancer, the relationship between pCR and EFS differs by tumor intrinsic subtype, and the benefit of dual vs. single HER2-blockade seems to be limited to HER2-Enriched subtype tumors. Immune signatures were associated with higher pCR rates and better EFS, luminal signatures were associated with lower pCR rates but good EFS outcomes, and vascular/proliferation/metastasis signatures were associated with poor EFS across the three clinical trials. Clinical trial identification: CALGB 40601: NCT00770809. (CALGB is part of the Alliance for Clinical Trials in Oncology). NeoALTTO: NCT00553358 NSABP B-41: NCT00486668

Spatial Characterization of Tumor-Infiltrating Lymphocytes and Breast Cancer Progression

Tumor-infiltrating lymphocytes (TILs) have been established as a robust prognostic biomarker in breast cancer, with emerging utility in predicting treatment response in the adjuvant and neoadjuvant settings. In this study, the role of TILs in predicting overall survival and progression-free interval was evaluated in two independent cohorts of breast cancer from the Cancer Genome Atlas (TCGA BRCA) and the Carolina Breast Cancer Study (UNC CBCS). We utilized machine learning and computer vision algorithms to characterize TIL infiltrates in digital whole-slide images (WSIs) of breast cancer stained with hematoxylin and eosin (H&E). Multiple parameters were used to characterize the global abundance and spatial features of TIL infiltrates. Univariate and multivariate analyses show that large aggregates of peritumoral and intratumoral TILs (forests) were associated with longer survival, whereas the absence of intratumoral TILs (deserts) is associated with increased risk of recurrence. Patients with two or more high-risk spatial features were associated with significantly shorter progression-free interval (PFI). This study demonstrates the practical utility of Pathomics in evaluating the clinical significance of the abundance and spatial patterns of distribution of TIL infiltrates as important biomarkers in breast cancer.

CALGB 40603 (Alliance): Long-Term Outcomes and Genomic Correlates of Response and Survival After Neoadjuvant Chemotherapy With or Without Carboplatin and Bevacizumab in Triple-Negative Breast Cancer

PURPOSE

CALGB 40603 (NCT00861705), a 2 × 2 randomized phase II trial, demonstrated that adding carboplatin or bevacizumab to weekly paclitaxel (wP) followed by doxorubicin and cyclophosphamide significantly increased the pathologic complete response (pCR) rate in stage II-III triple-negative breast cancer. We now report long-term outcomes (LTOs) and correlative science end points.

PATIENTS AND METHODS

The Kaplan-Meier method was used to estimate LTOs in 443 patients who initiated study treatment. Log-rank tests and Cox proportional hazards models evaluated the impact of clinical characteristics, pathologic response, calculated residual cancer burden (RCB) in patients with residual disease (RD), treatment assignment, and dose delivery during wP on LTOs, including event-free survival (EFS). Genomic predictors of treatment response and outcomes were assessed on pretreatment tumor samples by mRNA sequencing.

RESULTS

Among baseline characteristics, only the clinical stage was associated with LTOs. At a median follow-up of 7.9 years, LTOs were not significantly improved with either carboplatin or bevacizumab, overall or in patients with basal-like subtype cancers by genomic analysis. Patients with pCR (n = 205, 46.3%) had significantly higher 5-year EFS (85.5% v 56.6%, log-rank P < .0001) and overall survival (87.9% v 63.4%, P < .0001) rates compared with patients with RD, even those with RCB class I. Among clinical and genomic features, evidence of immune activation, including tumor-infiltrating lymphocytes and low B-cell receptor evenness, was associated with pCR and improved EFS.

CONCLUSION

Despite higher pCR rates, neither carboplatin nor bevacizumab appeared to improve LTOs although the study was not powered to assess these secondary end points. pCR was associated with superior LTOs even when compared with minimal RD. Markers of immune activation in pretreatment tumor biopsies were independently associated with higher pCR rates and improved survival.

Racial differences in breast cancer outcomes by hepatocyte growth factor pathway expression

PURPOSE

Black women have a 40% increased risk of breast cancer-related mortality. These outcome disparities may reflect differences in tumor pathways and a lack of targetable therapies for specific subtypes that are more common in Black women. Hepatocyte growth factor (HGF) is a targetable pathway that promotes breast cancer tumorigenesis, is associated with basal-like breast cancer, and is differentially expressed by race. This study assessed whether a 38-gene HGF expression signature is associated with recurrence and survival in Black and non-Black women.

METHODS

Study participants included 1957 invasive breast cancer cases from the Carolina Breast Cancer Study. The HGF signature was evaluated in association with recurrence (n = 1251, 171 recurrences), overall, and breast cancer-specific mortality (n = 706, 190/328 breast cancer/overall deaths) using Cox proportional hazard models.

RESULTS

Women with HGF-positive tumors had higher recurrence rates [HR 1.88, 95% CI (1.19, 2.98)], breast cancer-specific mortality [HR 1.90, 95% CI (1.26, 2.85)], and overall mortality [HR 1.69; 95% CI (1.17, 2.43)]. Among Black women, HGF positivity was significantly associated with higher 5-year rate of recurrence [HR 1.73; 95% CI (1.01, 2.99)], but this association was not significant in non-Black women [HR 1.68; 95% CI (0.72, 3.90)]. Among Black women, HGF-positive tumors had elevated breast cancer-specific mortality [HR 1.80, 95% CI (1.05, 3.09)], which was not significant in non-Black women [HR 1.52; 95% CI (0.78, 2.99)].

CONCLUSION

This multi-gene HGF signature is a poor-prognosis feature for breast cancer and may identify patients who could benefit from HGF-targeted treatments, an unmet need for Black and triple-negative patients.

BIDIMENSIONAL LINKED MATRIX FACTORIZATION FOR PAN-OMICS PAN-CANCER ANALYSIS

Several modern applications require the integration of multiple large data matrices that have shared rows and/or columns. For example, cancer studies that integrate multiple omics platforms across multiple types of cancer, pan-omics pan-cancer analysis, have extended our knowledge of molecular heterogeneity beyond what was observed in single tumor and single platform studies. However, these studies have been limited by available statistical methodology. We propose a flexible approach to the simultaneous factorization and decomposition of variation across such bidimensionally linked matrices, BIDIFAC+. BIDIFAC+ decomposes variation into a series of low-rank components that may be shared across any number of row sets (e.g., omics platforms) or column sets (e.g., cancer types). This builds on a growing literature for the factorization and decomposition of linked matrices which has primarily focused on multiple matrices that are linked in one dimension (rows or columns) only. Our objective function extends nuclear norm penalization, is motivated by random matrix theory, gives a unique decomposition under relatively mild conditions, and can be shown to give the mode of a Bayesian posterior distribution. We apply BIDIFAC+ to pan-omics pan-cancer data from TCGA, identifying shared and specific modes of variability across four different omics platforms and 29 different cancer types.

TP53 Pathway Function, Estrogen Receptor Status, and Breast Cancer Risk Factors in the Carolina Breast Cancer Study

BACKGROUND

TP53 and estrogen receptor (ER) both play essential roles in breast cancer development and progression, with recent research revealing cross-talk between TP53 and ER signaling pathways. Although many studies have demonstrated heterogeneity of risk factor associations across ER subtypes, associations by TP53 status have been inconsistent.

METHODS

This case-case analysis included incident breast cancer cases (47% Black) from the Carolina Breast Cancer Study (1993-2013). Formalin-fixed paraffin-embedded tumor samples were classified for TP53 functional status (mutant-like/wild-type-like) using a validated RNA signature. For IHC-based TP53 status, mutant-like was classified as at least 10% positivity. We used two-stage polytomous logistic regression to evaluate risk factor heterogeneity due to RNA-based TP53 and/or ER, adjusting for each other and for PR, HER2, and grade. We then compared this with the results when using IHC-based TP53 classification.

RESULTS

The RNA-based classifier identified 55% of tumors as TP53 wild-type-like and 45% as mutant-like. Several hormone-related factors (oral contraceptive use, menopausal status, age at menopause, and pre- and postmenopausal body mass index) were associated with TP53 mutant-like status, whereas reproductive factors (age at first birth and parity) and smoking were associated with ER status. Multiparity was associated with both TP53 and ER. When classifying TP53 status using IHC methods, no associations were observed with TP53. Associations observed with RNA-based TP53 remained after accounting for basal-like subtype.

CONCLUSIONS

This case-case study found breast cancer risk factors associated with RNA-based TP53 and ER.

IMPACT

RNA-based TP53 and ER represent an emerging etiologic schema of interest in breast cancer prevention research.

Molecular analysis of TCGA breast cancer histologic types

Breast cancer is classified into multiple distinct histologic types, and many of the rarer types have limited characterization. Here, we extend The Cancer Genome Atlas Breast Cancer (TCGA-BRCA) dataset with additional histologic type annotations, in a total of 1063 breast cancers. We analyze this extended dataset to define transcriptomic and genomic profiles of six rare special histologic types: cribriform, micropapillary, mucinous, papillary, metaplastic, and invasive carcinoma with medullary pattern. We show the broader applicability of our constructed special histologic type gene signatures in the TCGA Pan-Cancer Atlas dataset with a predictive model that detects mucinous histologic type across cancers of other organ systems. Using a normal mammary cell differentiation score analysis, we order histologic types into a continuum from stem cell-like to luminal progenitor-like to mature luminal-like. Finally, we classify TCGA-BRCA into 12 consensus groups based on integrated genomic and histological features. We present a rich openly accessible resource of histologic and genomic characterization of TCGA-BRCA to enable studies of the range of breast cancers.

JOINT AND INDIVIDUAL ANALYSIS OF BREAST CANCER HISTOLOGIC IMAGES AND GENOMIC COVARIATES

The two main approaches in the study of breast cancer are histopathology (analyzing visual characteristics of tumors) and genomics. While both histopathology and genomics are fundamental to cancer research, the connections between these fields have been relatively superficial. We bridge this gap by investigating the Carolina Breast Cancer Study through the development of an integrative, exploratory analysis framework. Our analysis gives insights - some known, some novel - that are engaging to both pathologists and geneticists. Our analysis framework is based on Angle-based Joint and Individual Variation Explained (AJIVE) for statistical data integration and exploits Convolutional Neural Networks (CNNs) as a powerful, automatic method for image feature extraction. CNNs raise interpretability issues that we address by developing novel methods to explore visual modes of variation captured by statistical algorithms (e.g. PCA or AJIVE) applied to CNN features.

UNMASC: tumor-only variant calling with unmatched normal controls

Despite years of progress, mutation detection in cancer samples continues to require significant manual review as a final step. Expert review is particularly challenging in cases where tumors are sequenced without matched normal control DNA. Attempts have been made to call somatic point mutations without a matched normal sample by removing well-known germline variants, utilizing unmatched normal controls, and constructing decision rules to classify sequencing errors and private germline variants. With budgetary constraints related to computational and sequencing costs, finding the appropriate number of controls is a crucial step to identifying somatic variants. Our approach utilizes public databases for canonical somatic variants as well as germline variants and leverages information gathered about nearby positions in the normal controls. Drawing from our cohort of targeted capture panel sequencing of tumor and normal samples with varying tumortypes and demographics, these served as a benchmark for our tumor-only variant calling pipeline to observe the relationship between our ability to correctly classify variants against a number of unmatched normals. With our benchmarked samples, approximately ten normal controls were needed to maintain 94% sensitivity, 99% specificity and 76% positive predictive value, far outperforming comparable methods. Our approach, called UNMASC, also serves as a supplement to traditional tumor with matched normal variant calling workflows and can potentially extend to other concerns arising from analyzing next generation sequencing data.

Identification of a Novel Inflamed Tumor Microenvironment Signature as a Predictive Biomarker of Bacillus Calmette-Guérin Immunotherapy in Non-Muscle-Invasive Bladder Cancer

PURPOSE

Improved risk stratification and predictive biomarkers of treatment response are needed for non-muscle-invasive bladder cancer (NMIBC). Here we assessed the clinical utility of targeted RNA and DNA molecular profiling in NMIBC.

EXPERIMENTAL DESIGN

Gene expression in NMIBC samples was profiled by NanoString nCounter, an RNA quantification platform, from two independent cohorts (n = 28, n = 50); targeted panel sequencing was performed in a subgroup (n = 50). Gene signatures were externally validated using two RNA sequencing datasets of NMIBC tumors (n = 438, n = 73). Established molecular subtype classifiers and novel gene expression signatures were assessed for associations with clinicopathologic characteristics, somatic tumor mutations, and treatment outcomes.

RESULTS

Molecular subtypes distinguished between low-grade Ta tumors with FGFR3 mutations and overexpression (UROMOL-class 1) and tumors with more aggressive clinicopathologic characteristics (UROMOL-classes 2 and 3), which were significantly enriched with TERT promoter mutations. However, UROMOL subclasses were not associated with recurrence after bacillus Calmette-Guérin (BCG) immunotherapy in two independent cohorts. In contrast, a novel expression signature of an inflamed tumor microenvironment (TME) was associated with improved recurrence-free survival after BCG. Expression of immune checkpoint genes (PD-L1/PD-1/CTLA-4) was associated with an inflamed TME, but not with higher recurrence rates after BCG. FGFR3 mutations and overexpression were both associated with low immune signatures.

CONCLUSIONS

Assessment of the immune TME, rather than molecular subtypes, is a promising predictive biomarker of BCG response. Modulating the TME in an immunologically "cold" tumor warrants further investigation. Integrated transcriptomic and exome sequencing should improve treatment selection in NMIBC.

Hepatocyte growth factor pathway expression in breast cancer by race and subtype

BACKGROUND

African American women have the highest risk of breast cancer mortality compared to other racial groups. Differences in tumor characteristics have been implicated as a possible cause; however, the tumor microenvironment may also contribute to this disparity in mortality. Hepatocyte growth factor (HGF) is a stroma-derived marker of the tumor microenvironment that may affect tumor progression differentially by race.

OBJECTIVE

To examine whether an HGF gene expression signature is differentially expressed by race and tumor characteristics.

METHODS

Invasive breast tumors from 1957 patients were assessed for a 38-gene RNA-based HGF gene expression signature. Participants were black (n = 1033) and non-black (n = 924) women from the population-based Carolina Breast Cancer Study (1993-2013). Generalized linear models were used to estimate the relative frequency differences (RFD) in HGF status by race, clinical, and demographic factors.

RESULTS

Thirty-two percent of tumors were positive for the HGF signature. Black women were more likely [42% vs. 21%; RFD = + 19.93% (95% CI 16.00, 23.87)] to have HGF-positive tumors compared to non-black women. Triple-negative patients had a higher frequency of HGF positivity [82% vs. 13% in non-triple-negative; RFD = + 65.85% (95% CI 61.71, 69.98)], and HGF positivity was a defining feature of basal-like subtype [92% vs. 8% in non-basal; RFD = + 81.84% (95% CI 78.84, 84.83)]. HGF positivity was associated with younger age, stage, higher grade, and high genomic risk of recurrence (ROR-PT) score.

CONCLUSION

HGF expression is a defining feature of basal-like tumors, and its association with black race and young women suggests it may be a candidate pathway for understanding breast cancer disparities.

Abstract 2188: Urothelial cancer-GENOmic analysis to improve patient outcomes and research (UC-GENOME): a bladder cancer advocacy network (BCAN) led collaborative research study

The UC-GENOME study was designed to capitalize on The Cancer Genome Atlas (TCGA) findings in real world patients with metastatic urothelial carcinoma (UC) with co-equal aims: 1) to provide targeted DNA sequencing for potential clinical decision making at no cost to patients; and 2) to create a clinically annotated biorepository (including tissue, plasma, and PBMCs) for collaborative research. Patients with metastatic UC (n=209, median age 68 y, 74% male) were accrued at 8 academic medical centers between 2016-2019. We report on the first analysis of the targeted DNAseq (n=191) and total RNAseq (n=176) from FFPE specimens (n=169 overlap). Recurrently mutated genes were observed in a similar frequency to TCGA, including TP53 (54%), KMT2D (30%), ARID1A (26%) and FGFR3 (18%). Somatic variant patterns were correlated with previously annotated mutational signatures (COSMICv3), revealing a subset of tumors enriched for APOBEC signatures. Molecular subtypes were defined using the Bladder Cancer Molecular Taxonomy Group's consensus subtyping schema (Ba_Sq=54 [31%], Stroma-rich=64 [36%], LumP=26 [15%], LumU=24 [14%], LumNS=4 [2%], NE=4 [2%]). To further understand the tumor immune features and whether they correlate with durable clinical response, tumor microenvironment deconvolution was performed by applying MiXCR and immune gene signatures. An inflamed phenotype and enhanced T cell receptor richness but not clonality was observed within Ba_Sq and Stroma-rich subtypes, which also had the highest disease control rate (CR/PR + SD ~75%) to immunotherapy. The Stroma-rich subtype had the highest disease control rate (~88%) to chemotherapy. Future efforts will leverage the clinical, DNA and RNAseq data along with other biobanked specimens for collaborative research initiatives.

Citation Format: Jeffrey S. Damrauer, Jeff Klomp, Wolfgang Beck, Mi Zhou, Elizabeth Plimack, Matthew Galsky, Petros Grivas, Noah Hahn, Peter O'Donnell, Gopa Iyer, David I. Quinn, Katherine A. Hoadley, William Y. Kim, Matthew I. Milowsky. Urothelial cancer-GENOmic analysis to improve patient outcomes and research (UC-GENOME): a bladder cancer advocacy network (BCAN) led collaborative research study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2188.

Protein-based immune profiles of basal-like vs. luminal breast cancers

Tumor-infiltrating lymphocytes play an important, but incompletely understood role in chemotherapy response and prognosis. In breast cancer, there appear to be distinct immune responses by subtype, but most studies have used limited numbers of protein markers or bulk sequencing of RNA to characterize immune response, in which spatial organization cannot be assessed. To identify immune phenotypes of Basal-like vs. Luminal breast cancer we used the GeoMx® (NanoString) platform to perform digital spatial profiling of immune-related proteins in tumor whole sections and tissue microarrays (TMA). Visualization of CD45, CD68, or pan-Cytokeratin by immunofluorescence was used to select regions of interest in formalin-fixed paraffin embedded tissue sections. Forty-four antibodies representing stromal markers and multiple immune cell types were applied to quantify the tumor microenvironment. In whole tumor slides, immune hot spots (CD45+) had increased expression of many immune markers, suggesting a diverse and robust immune response. In epithelium-enriched areas, immune signals were also detectable and varied by subtype, with regulatory T-cell (Treg) markers (CD4, CD25, and FOXP3) being higher in Basal-like vs. Luminal breast cancer. Extending these findings to TMAs with more patients (n = 75), we confirmed subtype-specific immune profiles, including enrichment of Treg markers in Basal-likes. This work demonstrated that immune responses can be detected in epithelium-rich tissue, and that TMAs are a viable approach for obtaining important immunoprofiling data. In addition, we found that immune marker expression is associated with breast cancer subtype, suggesting possible prognostic, or targetable differences.

An approach for normalization and quality control for NanoString RNA expression data

The NanoString RNA counting assay for formalin-fixed paraffin embedded samples is unique in its sensitivity, technical reproducibility and robustness for analysis of clinical and archival samples. While commercial normalization methods are provided by NanoString, they are not optimal for all settings, particularly when samples exhibit strong technical or biological variation or where housekeeping genes have variable performance across the cohort. Here, we develop and evaluate a more comprehensive normalization procedure for NanoString data with steps for quality control, selection of housekeeping targets, normalization and iterative data visualization and biological validation. The approach was evaluated using a large cohort ($N=\kern0.5em 1649$) from the Carolina Breast Cancer Study, two cohorts of moderate sample size ($N=359$ and$130$) and a small published dataset ($N=12$). The iterative process developed here eliminates technical variation (e.g. from different study phases or sites) more reliably than the three other methods, including NanoString's commercial package, without diminishing biological variation, especially in long-term longitudinal multiphase or multisite cohorts. We also find that probe sets validated for nCounter, such as the PAM50 gene signature, are impervious to batch issues. This work emphasizes that systematic quality control, normalization and visualization of NanoString nCounter data are an imperative component of study design that influences results in downstream analyses.

Integrative modeling identifies genetic ancestry-associated molecular correlates in human cancer

Cellular and molecular aberrations contribute to the disparity of human cancer incidence and etiology between ancestry groups. Multiomics profiling in The Cancer Genome Atlas (TCGA) allows for querying of the molecular underpinnings of ancestry-specific discrepancies in human cancer. Here, we provide a protocol for integrative associative analysis of ancestry with molecular correlates, including somatic mutations, DNA methylation, mRNA transcription, miRNA transcription, and pathway activity, using TCGA data. This protocol can be generalized to analyze other cancer cohorts and human diseases.

For complete details on the use and execution of this protocol, please refer to Carrot-Zhang et al. (2020).

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Protocols for ancestry associations with TCGA molecular data

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Protocols for ancestry associations with oncogenic pathways

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Statistical and power analysis for determining significant associations

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Key considerations of potential confounding factors

Abstract SS1-05: Racial differences in breast cancer immune microenvironments

Background: Black women suffer 40% higher mortality from breast cancer (BC) compared to non-Hispanic white women, and the underlying causes of these disparities remain uncertain. Growing evidence supports the importance of the immune microenvironment in BC survival, but immune response differences by race are poorly understood. We sought to characterize the immune microenvironment of BC to evaluate how phenotypes of immune response vary across race and tumor intrinsic subtype to impact clinical outcomes. Methods: We leveraged the Carolina Breast Cancer Study (CBCS), a large population-based study that oversampled young (≤50) and black women with invasive breast cancer and collected tumor tissue on &gt;95% of participants. We curated a 48-gene panel representative of 13 individual immune cell types, and performed NanoString gene expression profiling on tissue from 1957 BC patients, including 1033 (53%) Black and 924 (47%) Non-Black women. Consensus clustering was used to identify phenotypes of immune response, and individual immune cell scores were calculated as the median expression of cell-type markers. Immune phenotypes and cell-type scores were compared against validated protein markers and H&E-based quantification of TILs from corresponding tissue microarrays (TMAs). We estimated associations of immune classes with BC intrinsic subtype, ROR-PT scores (calculated as low, medium and high), age and race using relative frequency differences (RFDs), adjusting for age and tumor stage. Cell type scores were compared by race using Welch’s t-tests and adjusted for multiple comparisons with the Benjamani-Hochberg procedure. Results: We identified three BC immune phenotypes primarily defined by features related to an Adaptive-enriched, Innate-enriched, or a Quiet immune microenvironment. These expression-based groups correlated with histological evidence of immune cells from corresponding TMAs. Similarly, expression-based cell scores correlated strongly with protein-based quantification of immune cells from corresponding TMAs (e.g. B-cell score vs. CD19 immunofluorescence, rho=0.75; ICOS RNA counts vs. protein; Rho=0.76). Both Adaptive-enriched and Innate-enriched tumors were associated with high ROR-PT scores [RFD for Adaptive-enriched vs. Quiet: 24.1% (95% CI 19.3-28.8); Innate-enriched vs. Quiet RFD: 13.1 (95% CI 9.1-17); frequencies: 37.2%, 26.2% and 10% for Adaptive, Innate and Quiet, respectively], the basal-like intrinsic subtype [RFD for Adaptive-enriched vs. Quiet: 19.4% (95% CI 14.3-24.6); Innate-enriched vs. Quiet RFD: 9.8 (95% CI 5.6-14.1); frequencies: 43.4%, 27.4% and 8.9% respectively] and Black race [RFD for Adaptive-enriched vs. Quiet: 16.1% (95% CI 10.3-21.9); Innate-enriched vs. Quiet RFD: 9.5 (95% CI 3.9-15); frequencies 60.5%, 53.5% and 42.5% respectively]. After adjusting for tumor subtype, the Adaptive-enriched class remained associated with Black race (RFD for Adaptive-Enriched vs Quiet: 7.5% (95% CI 1.4-13.6). Conversely, tumors in the immune-quiet group were primarily non-basal (90%) with low ROR-PT scores (86.7%). Within the Adaptive-enriched class, Black women displayed decreased CD8 T cell scores (p=0.05) but increased T-reg cell scores (p=0.02) relative to Non-Black women. Conclusion: Immune response appears to be intricately related to race and tumor subtype, with black women having strong associations with adaptive-enriched and innate-enriched immune microenvironments. Differences in CD8 T cell and Treg expression suggest that even within broad classes of immune response, racial differences in specific cell-type distributions exist. Immune response differences may be targetable to improve treatment response, and therefore it is important to identify race- and subtype-specific differences in immune microenvironments.

Citation Format: Alina M Hamilton, Linnea T Olsson, Benjamin C Calhoun, Katherine A Hoadley, Melissa A Troester. Racial differences in breast cancer immune microenvironments [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr SS1-05.

Abstract PS19-03: Dna repair imbalance and immune response in breast cancer mortality disparities

Background: Black breast cancer patients have p53 loss in 60% of their tumors, compared to 35% p53 loss in white breast cancer patients. The tumor suppressor p53 has pleiotropic effects on DNA repair, as it regulates both error prone and error-free DNA repair pathways. These effects on DNA repair represent molecular vulnerabilities that influence chemotherapy response, both directly and indirectly through the activation of immune responses. While studies have begun to elucidate DNA repair imbalance and immune response in human cancer, little is known about how these pathways differ by race. Methods: To study DNA repair and immune response in breast cancer, we performed gene expression analysis on FFPE samples from the Carolina Breast Cancer Study (CBCS), a large population-based study that oversampled black and younger women. We curated a list of DNA repair genes representing regulators of error prone and error free DNA repair. Pathways included Nucleotide Excision Repair (NER), Fanconi Anemia (FA), Mismatch repair (MMR), Base Excision Repair (BER), Homologous Recombination (HR), Translesion Synthesis (TLS), Alternative End Joining (AEJ), Checkpoint, and APOBEC. In addition, we developed a 50-gene immune panel representing 12 individual immune cell types (B cells, T cells, Treg cells, T help cells, T follicular helper cells, CD8 T cells, NK cells, Eosinophils, Neutrophils, M1 & M2 Macrophages) and both adaptive and innate arms of the immune system. A total of 1464 patients (53% black, 53% under 50) were included in the current analysis. We used consensus clustering to identify groups of patients based on DNA repair gene expression and used linear regression to estimate the relative frequency differences between these classes and demographic and clinical characteristics. Results: We found that breast cancers grouped into four clusters based on DNA repair gene expression. One cluster, ‘Repair High’, represented 32% of the tumors, and had high expression of NER, NHEJ, HR, and FA genes, suggesting a broad DNA repair response. Another group, ‘HR/FA High’ represented 23% of the tumors and was enriched for high expression of HR and FA genes. An “APOBEC High” group consisted of 32% of the tumors and was enriched for high expression of APOBEC family genes (APOBEC3D, APOBEC1, APOBEC3A, APOBEC3H, APOBEC3B). Finally, 13% of tumors, had a ‘Heterogeneous Repair’ pattern of high expression of HR, NHEJ, and FA genes, but lower expression of NER genes. The HR/FA and Heterogeneous Repair groups were enriched for TP53 mutant-like tumors (93% vs. 5% and 61% vs. 38% Mutant vs. Wildtype respectively). In addition, the Heterogeneous Repair group was enriched for Hormone Receptor positive samples ([RFD] 8.2% (0.613, 15.3), 77% vs. 23% in positive vs. negative respectively), while the HR/FA High group was significantly enriched for TNBC ([RFD] HR/FA: 51.2% (45.1, 57.1), 75% vs. 25% TNBC vs. non-TNBC respectively). The Repair High group was the only group enriched for non-black race ([RFD]: 10.4% (4.0, 16.7), 42% vs. 58% in blacks vs. non-blacks respectively). Finally, DNA repair classes were associated with immune scores, with the APOBEC High tumors having a significantly higher Eosinophil score (p = 0.021) and Neutrophil score (p = 0.007) compared to the other four groups. Conclusion: DNA repair expression is highly variable across breast tumors and may depend upon TP53 status, tumor subtype, and race. Differential immune marker expression by DNA repair group suggests some DNA repair groups may have differential response to immune-targeted therapies. DNA repair, immune response, and race are inter-related in breast cancer and unraveling and ultimately targeting breast cancer disparities may require coordinated evaluation of these pathways.

Citation Format: Andrea Walens, Alina M Hamilton, Markia A Smith, Xiaohua Gao, Erin L Kirk, Stephen D Hursting, Katherine A Hoadley, Cyrus Vaziri, Melissa A Troester. Dna repair imbalance and immune response in breast cancer mortality disparities [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS19-03.

Whole-genome characterization of lung adenocarcinomas lacking the RTK/RAS/RAF pathway

RTK/RAS/RAF pathway alterations (RPAs) are a hallmark of lung adenocarcinoma (LUAD). In this study, we use whole-genome sequencing (WGS) of 85 cases found to be RPA(-) by previous studies from The Cancer Genome Atlas (TCGA) to characterize the minority of LUADs lacking apparent alterations in this pathway. We show that WGS analysis uncovers RPA(+) in 28 (33%) of the 85 samples. Among the remaining 57 cases, we observe focal deletions targeting the promoter or transcription start site of STK11 (n = 7) or KEAP1 (n = 3), and promoter mutations associated with the increased expression of ILF2 (n = 6). We also identify complex structural variations associated with high-level copy number amplifications. Moreover, an enrichment of focal deletions is found in TP53 mutant cases. Our results indicate that RPA(-) cases demonstrate tumor suppressor deletions and genome instability, but lack unique or recurrent genetic lesions compensating for the lack of RPAs. Larger WGS studies of RPA(-) cases are required to understand this important LUAD subset.

SCISSOR: a framework for identifying structural changes in RNA transcripts

High-throughput sequencing protocols such as RNA-seq have made it possible to interrogate the sequence, structure and abundance of RNA transcripts at higher resolution than previous microarray and other molecular techniques. While many computational tools have been proposed for identifying mRNA variation through differential splicing/alternative exon usage, challenges in its analysis remain. Here, we propose a framework for unbiased and robust discovery of aberrant RNA transcript structures using short read sequencing data based on shape changes in an RNA-seq coverage profile. Shape changes in selecting sample outliers in RNA-seq, SCISSOR, is a series of procedures for transforming and normalizing base-level RNA sequencing coverage data in a transcript independent manner, followed by a statistical framework for its analysis ( https://github.com/hyochoi/SCISSOR ). The resulting high dimensional object is amenable to unsupervised screening of structural alterations across RNA-seq cohorts with nearly no assumption on the mutational mechanisms underlying abnormalities. This enables SCISSOR to independently recapture known variants such as splice site mutations in tumor suppressor genes as well as novel variants that are previously unrecognized or difficult to identify by any existing methods including recurrent alternate transcription start sites and recurrent complex deletions in 3' UTRs.

Molecular Features of Cancers Exhibiting Exceptional Responses to Treatment

A small fraction of cancer patients with advanced disease survive significantly longer than patients with clinically comparable tumors. Molecular mechanisms for exceptional responses to therapy have been identified by genomic analysis of tumor biopsies from individual patients. Here, we analyzed tumor biopsies from an unbiased cohort of 111 exceptional responder patients using multiple platforms to profile genetic and epigenetic aberrations as well as the tumor microenvironment. Integrative analysis uncovered plausible mechanisms for the therapeutic response in nearly a quarter of the patients. The mechanisms were assigned to four broad categories-DNA damage response, intracellular signaling, immune engagement, and genetic alterations characteristic of favorable prognosis-with many tumors falling into multiple categories. These analyses revealed synthetic lethal relationships that may be exploited therapeutically and rare genetic lesions that favor therapeutic success, while also providing a wealth of testable hypotheses regarding oncogenic mechanisms that may influence the response to cancer therapy.