Establishing guidelines to harmonize tumor mutational burden (TMB): in silico assessment of variation in TMB quantification across diagnostic platforms: phase I of the Friends of Cancer Research TMB Harmonization Project

Molecular profiling METex14+ non-small cell lung cancer (NSCLC): Impact of histology

OBJECTIVES

MET exon 14 skipping alterations (METex14+) represent a heterogeneous subgroup of non-small cell lung cancer (NSCLC) with distinct biological and genomic features. We characterized this heterogeneity in a large cohort, integrating genomic and transcriptomic profiling with clinical outcomes, to elucidate the histologic and molecular traits and survival patterns of METex14+ NSCLC.

MATERIALS AND METHODS

NSCLC tissue samples (n = 28,739) underwent DNA-based next-generation sequencing (592 genes, NextSeq) or whole-exome sequencing (NovaSeq), RNA-sequencing including whole transcriptome sequencing (WTS, NovaSeq), and PD-L1 IHC (Dako 22C3) at Caris Life Sciences. Immune cell fractions were estimated from bulk RNA sequencing (quanTIseq). Real-world survival data (mOS) was calculated from insurance claims. Statistical analyses employed Chi-square, Fisher's exact, or Mann-Whitney U and log-rank tests and were corrected for hypothesis testing where applicable.

RESULTS

A total of 711 METex14+ cases were detected. Of 575 cases of defined histology, 77 (13.6 %) were squamous (Sq), 474 (82.3 %) were nSq (non-squamous), and 24 (4.1 %) were adenosquamous. Mutations in POT1 and BRCA2 were enriched, and amplifications in MDM2, HMGA2, CDK4, and MET were common in METex14+ tumors. TMB-high and TP53 mutated tumors were reduced in METex14+ independent of histology. KEAP1 (2.1 vs 14.7 %) and STK11 mutations (0.8 vs 17.1 %) were reduced only in METex14+ nSq (vs METex14+ Sq, q < 0.05). While the prevalence of PD-L1 high tumors was enriched in METex14+ independent of histology, T-cell inflamed tumors were enriched only in nSq METex14+. B-cells and CD8+ T-cells (1.07-1.43-fold) were enriched in nSq METex14+, and dendritic cells (0.32 fold) were reduced only in METex14+ Sq. METex14+ tumors had a modest improvement in mOS compared to METex14- tumors (mOS = 22.9 m vs 18.6 m, HR = 0.914, p = 0.04). Moreover, METex14+ tumors who received immunotherapy (IO) had a modest improvement in survival (mOS = 27.5 m vs 21.8 m; HR = 0.803, p = 0.03) compared to those who did not receive IO. METex14+ nSq tumors were associated with improved mOS compared to METex14+ Sq tumors (mOS = 27.7 vs 8.9 m, HR = 0.493, p < 0.0001).

CONCLUSION

METex14+ alterations are a heterogeneous subgroup of NSCLC. Our analysis reveals that METex14+ nSq exhibit improved survival compared to METex14+ Sq. The distinct genomic and transcriptomic variations across histologies warrant clinical consideration.

Identification of immunity- and ferroptosis-related signature genes as potential design targets for mRNA vaccines in AML patients

Immune-associated ferroptosis plays an important role in the progression of acute myeloid leukemia (AML); however, the targets that play key roles in this process are currently unknown. This limits the development of mRNA vaccines based on immune-associated ferroptosis for clinical therapeutic applications. In this study, based on the rich data resources of the TCGA-LAML cohort, we analyzed the tumor mutational burden (TMB), gene mutation status, and associations between immune and ferroptosis genes to reveal the disease characteristics of AML patients. To gain a deeper understanding of differentially expressed genes, we applied the Limma package for differential expression analysis and integrated data sources such as ImmPort Shared Data and FerrDb V2. Moreover, we established gene modules related to TMB according to weighted gene coexpression network analysis (WGCNA) and explored the functions of these modules in AML and their relationships with TMB. We focused on the top 30 most frequent genes through a detailed survey of missense mutations and single nucleotide polymorphisms (SNPs) and selected potentially critical gene targets for subsequent analysis. Based on the expression of these genes, we successfully subgrouped AML patients and found that the subgroups associated with TMB (C1 and C2) exhibited significant differences in survival. The differences in the tumor microenvironment and immune cells between C1 and C2 patients were investigated with the ESTIMATE and MCP-counter algorithms. A predictive model of TMB-related genes (TMBRGs) was constructed, and the validity of the model was demonstrated by categorizing patients into high-risk and low-risk groups. The differences in survival between the high-risk patients and high-TMB patients were further investigated, and potential vaccine targets were identified via immune cell-level analysis. The identification of immunity- and ferroptosis-associated signature genes is an independent predictor of survival in AML patients and provides new information on immunotherapy for AML.

Tumour mutational burden: clinical utility, challenges and emerging improvements

Tumour mutational burden (TMB), defined as the total number of somatic non-synonymous mutations present within the cancer genome, varies across and within cancer types. A first wave of retrospective and prospective research identified TMB as a predictive biomarker of response to immune-checkpoint inhibitors and culminated in the disease-agnostic approval of pembrolizumab for patients with TMB-high tumours based on data from the Keynote-158 trial. Although the applicability of outcomes from this trial to all cancer types and the optimal thresholds for TMB are yet to be ascertained, research into TMB is advancing along three principal avenues: enhancement of TMB assessments through rigorous quality control measures within the laboratory process, including the mitigation of confounding factors such as limited panel scope and low tumour purity; refinement of the traditional TMB framework through the incorporation of innovative concepts such as clonal, persistent or HLA-corrected TMB, tumour neoantigen load and mutational signatures; and integration of TMB with established and emerging biomarkers such as PD-L1 expression, microsatellite instability, immune gene expression profiles and the tumour immune contexture. Given its pivotal functions in both the pathogenesis of cancer and the ability of the immune system to recognize tumours, a profound comprehension of the foundational principles and the continued evolution of TMB are of paramount relevance for the field of oncology.

The Genetic Analysis and Clinical Therapy in Lung Cancer: Current Advances and Future Directions

Lung cancer, including both non-small cell lung cancer and small cell lung cancer, remains the leading cause of cancer-related mortality worldwide, representing 18% of the total cancer deaths in 2020. Many patients are identified already at an advanced stage with metastatic disease and have a worsening prognosis. Recent advances in the genetic understanding of lung cancer have opened new avenues for personalized treatments and targeted therapies. This review examines the latest discoveries in the genetics of lung cancer, discusses key biomarkers, and analyzes current clinical therapies based on this genetic information. It will conclude with a discussion of future prospects and potential research directions.

Multimodal analysis unveils tumor microenvironment heterogeneity linked to immune activity and evasion

The cellular and molecular heterogeneity of tumors is a major obstacle to cancer immunotherapy. Here, we use a systems biology approach to derive a signature of the main sources of heterogeneity in the tumor microenvironment (TME) from lung cancer transcriptomics. We demonstrate that this signature, which we called iHet, is conserved in different cancers and associated with antitumor immunity. Through analysis of single-cell and spatial transcriptomics data, we trace back the cellular origin of the variability explaining the iHet signature. Finally, we demonstrate that iHet has predictive value for cancer immunotherapy, which can be further improved by disentangling three major determinants of anticancer immune responses: activity of immune cells, immune infiltration or exclusion, and cancer-cell foreignness. This work shows how transcriptomics data can be integrated to derive a holistic representation of the phenotypic heterogeneity of the TME and to predict its unfolding and fate during immunotherapy with immune checkpoint blockers.

Genetic Analysis of Melanoma Types Using Japanese Genomic Database

OBJECTIVES

The purpose of this study is to compare genetic mutations, tumor mutation burden (TMB), and the effects of molecular targeted drugs and immune checkpoint inhibitors (ICIs) in head and neck mucosal melanoma (HNMUM) with those in skin melanoma (SKM) and ocular melanoma (OM).

METHODS

Data were analyzed for 72 consecutive patients with HNMUM, including 366 with SKM and 31 with OM, registered at the Japan National Cancer Center, Center for Cancer Genomics and Advanced Therapeutics (C-CAT) between June 2019 and October 2023. Genetic alterations and TMB were determined by FoundationOne CDx next-generation sequencing.

RESULTS

The top 10 mutations in HNMUM were RAD21 (47.2%), NBN (45.8%), MYC (40.3%), LYN (31.9%), NRAS (29.1%), IRF4 (23.6%), DAXX (22.2%), KIT (22.2%), NOTCH3 (20.8%), and DDR1 (19.4%), with 16.6 ± 0.8 (mean ± SEM) mutations/individual. In SKM, BRAF (p = 0.04) mutation was associated with a significantly better prognosis. The TMB values were 5.7 ± 2.1 (mean ± SEM) in HNMUM, 4.1 ± 0.2 in SKM, and 3.4 ± 0.9 in OM, with no significant differences among the three groups. The median survival time for patients with distant metastases was 803 (95% confidence interval: 539-NA) days for HNMUM, 1413 (831-2172) days for SKM, and 1138 (438-NA) days for OM.

CONCLUSIONS

The top 10 mutations in HNMUM are closer to those in OM than those in SKM. There was no significant difference in TMB values or survival rates with regard to the therapeutic effect of ICIs among the diseases, which suggests that current treatment of HNMUM with ICIs is appropriate.

LEVEL OF EVIDENCE

3 Laryngoscope, 2024.

Plasma versus Tissue Tumor Mutational Burden as Biomarkers of Durvalumab plus Tremelimumab Response in Patients with Metastatic Colorectal Cancer in the CO.26 Trial

PURPOSE

Tissue-derived tumor mutation burden (TMB) of ≥10 mutations/Mb is a histology-agnostic biomarker for the immune checkpoint inhibitor (ICI) pembrolizumab. However, the dataset in which this was validated lacked colorectal cancers (CRC), and there is limited evidence for immunotherapy benefits in CRC using this threshold.

PATIENTS AND METHODS

CO.26 was a randomized phase II study of 180 patients, comparing durvalumab and tremelimumab (D + T, n = 119 patients) versus best supportive care (BSC; n = 61 patients). ctDNA sequencing was available for 168 patients (n = 118 D + T; n = 50), of whom 165 had evaluable plasma TMB (pTMB). Tissue sequencing was available for 108 patients. Optimal thresholds for stratifying patients based on OS were determined using a minimal P value approach. This report includes the final OS analysis.

RESULTS

Tissue TMB ≥10 mutations/Mb was not predictive of benefit from D + T compared with BSC in microsatellite stable (MSS) metastatic CRC [HR, 0.71 (95% CI, 0.28-1.80); P = 0.47]. No tissue TMB threshold could identify a high TMB group that benefited from ICI. By contrast, plasma TMB (pTMB) ≥28 mutations/Mb was predictive of benefit from D + T [HR, 0.34 (95% CI, 0.13-0.85); P = 0.022], as was clonal pTMB ≥10.6 mutations/Mb [HR, 0.10 (95% CI, 0.014-0.79); P = 0.029] and subclonal pTMB ≥25.9/Mb [HR, 0.20 (95% CI, 0.061-0.69); P = 0.010]. Higher pTMB was associated with length of time on cytotoxic agents (P = 0.021) and prior anti-EGFR exposure (P = 2.44 × 10-06).

CONCLUSIONS

pTMB derived from either clonal or subclonal mutations may identify a group likely to benefit from immunotherapy, although validation is required. Tissue TMB provided no predictive utility for immunotherapy in this trial.

Recommendations for Tumor Mutational Burden Assay Validation and Reporting: A Joint Consensus Recommendation of the Association for Molecular Pathology, College of American Pathologists, and Society for Immunotherapy of Cancer

Tumor mutational burden (TMB) has been recognized as a predictive biomarker for immunotherapy response in several tumor types. Several laboratories offer TMB testing, but there is significant variation in how TMB is calculated, reported, and interpreted among laboratories. TMB standardization efforts are underway, but no published guidance for TMB validation and reporting is currently available. Recognizing the current challenges of clinical TMB testing, the Association for Molecular Pathology convened a multidisciplinary collaborative working group with representation from the American Society of Clinical Oncology, the College of American Pathologists, and the Society for the Immunotherapy of Cancer to review the laboratory practices surrounding TMB and develop recommendations for the analytical validation and reporting of TMB testing based on survey data, literature review, and expert consensus. These recommendations encompass pre-analytical, analytical, and postanalytical factors of TMB analysis, and they emphasize the relevance of comprehensive methodological descriptions to allow comparability between assays.

LORIS robustly predicts patient outcomes with immune checkpoint blockade therapy using common clinical, pathologic and genomic features

Despite the revolutionary impact of immune checkpoint blockade (ICB) in cancer treatment, accurately predicting patient responses remains challenging. Here, we analyzed a large dataset of 2,881 ICB-treated and 841 non-ICB-treated patients across 18 solid tumor types, encompassing a wide range of clinical, pathologic and genomic features. We developed a clinical score called LORIS (logistic regression-based immunotherapy-response score) using a six-feature logistic regression model. LORIS outperforms previous signatures in predicting ICB response and identifying responsive patients even with low tumor mutational burden or programmed cell death 1 ligand 1 expression. LORIS consistently predicts patient objective response and short-term and long-term survival across most cancer types. Moreover, LORIS showcases a near-monotonic relationship with ICB response probability and patient survival, enabling precise patient stratification. As an accurate, interpretable method using a few readily measurable features, LORIS may help improve clinical decision-making in precision medicine to maximize patient benefit. LORIS is available as an online tool at https://loris.ccr.cancer.gov/ .

Kinetic Profiling of RAS Mutations With Circulating Tumor DNA in the Canadian Cancer Trials Group CO.26 Trial Suggests the Loss of RAS Mutations in Neo-RAS-Wildtype Metastatic Colorectal Cancer Is Transient

PURPOSE

In metastatic colorectal cancer (mCRC), RAS mutations drive resistance to anti-epidermal growth factor receptor antibodies. It is unclear whether RAS mutations ever become clonally undetectable.

METHODS

CO.26 was a phase II clinical trial that assessed durvalumab + tremelimumab in heavily pretreated mCRC. RAS mutation status was tracked over time using circulating tumor DNA (ctDNA) sequencing at baseline, week 8, and on progression.

RESULTS

Among the 95 patients with KRAS/NRAS mutations in their archival tumor tissue, 6.3% (6/95) had undetectable RAS mutations in ctDNA collected at baseline or week 8 of the CO.26 study. Of these, 67% (4/6) of disappearances were transient, with the same mutation reappearing with progressive disease. In three cases, the simultaneous persistence of other preexisting CRC-associated truncal mutations could not be demonstrated, suggestive of low tumor shedding of ctDNA, leaving the incidence of true clonal reversion to RAS-wildtype (WT) possibly as low as 3.2% (3/95). Fewer patients in the neo-RAS-WT group (33%) had greater than four lesions at trial baseline compared with patients with persistent RAS mutations (75%), P = .046. The likelihood of synchronous metastases at cancer diagnosis (33% v 63%; P = .15) or liver metastases at trial baseline (50% v 68.5%; P = .17) was not significantly different between patients with disappearing versus persistent RAS mutations. Overall survival from stage IV diagnosis (hazard ratio, 0.77 [95% CI, 0.35 to 1.72]; P = .52) was not significantly different between those with disappearing versus persistent RAS mutations. The disappearance of RAS mutations was not associated with primary tumor sidedness (P = .41), archival BRAF/MEK/ERK-mutant status (P = .16/1.00/.09), nor baseline ctDNA HER2 amplifications (P = 1.00).

CONCLUSION

We identified a 3.2%-6.3% prevalence of the neo-RAS-WT phenomenon in the CO.26 trial. However, 67% of apparent cases were transient with subsequent re-emergence.

The Genomic Landscape of Breast Cancer in Young and Older Women

BACKGROUND

Young women with breast cancer (YWBC; ≤40 years) often have a poorer prognosis than older women with breast cancer (OWBC; ≥65 years). We explored molecular features of tumors from YWBC and OWBC to identify a biologic connection for these patterns.

MATERIALS AND METHODS

We retrospectively analyzed the molecular profiles of 1879 breast tumors. Testing included immunohistochemistry (IHC), in situ hybridization (ISH), and next-generation sequencing. Statistical analyses included Pearson's chi2 test for comparisons, with significance defined as FDR (false discovery rate)-P < .05.

RESULTS

TP53 and BRCA1 somatic mutations were more common in YWBC tumors than in OWBC tumors (53%, 42%; P = .0001, FDR-P = .0025 and 7%, 2%; P = .0001, FDR-P = .0025; respectively). Conversely, OWBC tumors had higher androgen receptor expression (55%, 45%; P = .0002, FDR-P = .0025) higher PD-L1 expression detected by IHC (8%, 5%; P = .0476, FDR-P = .2754), and more frequent PIK3CA mutations (33%, 17%; P = < .0001, FDR-P = < .0001). Among HR+/HER2- samples, YWBC had more gene amplifications in FGF3 (27%, 10%; P = .0353, FDR-P = .2462), FGF4 (27%, 9%; P = .0218, FDR-P = .1668), FGF19 (30%, 12%; P = .034, FDR-P = .2462) and CCND1 (37%, 18%; P = .0344, FDR-P = .2462) than OWBC.

CONCLUSIONS

Our data suggest distinct molecular aberrations exist between YWBC and OWBC. Exploiting these molecular changes could refine our treatment strategies in YWBC and OWBC.

Biomarker development for PD-(L)1 axis inhibition: a consensus view from the SITC Biomarkers Committee

Therapies targeting the programmed cell death protein-1/programmed death-ligand 1 (PD-L1) (abbreviated as PD-(L)1) axis are a significant advancement in the treatment of many tumor types. However, many patients receiving these agents fail to respond or have an initial response followed by cancer progression. For these patients, while subsequent immunotherapies that either target a different axis of immune biology or non-immune combination therapies are reasonable treatment options, the lack of predictive biomarkers to follow-on agents is impeding progress in the field. This review summarizes the current knowledge of mechanisms driving resistance to PD-(L)1 therapies, the state of biomarker development along this axis, and inherent challenges in future biomarker development for these immunotherapies. Innovation in the development and application of novel biomarkers and patient selection strategies for PD-(L)1 agents is required to accelerate the delivery of effective treatments to the patients most likely to respond.

Study of sex-biased differences in genomic profiles in East Asian hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is characterized by a notable sex disparity in incidence and tumor aggressiveness. Revealing differences in genetic landscapes between male and female HCCs may expand the understanding of sexual disparities mechanisms and assist the development of precision medicine. Although reports on the sex disparity of HCC are accumulated, studies focusing on sex-related biomarkers among Asian populations remain limited. Here, we conducted a comprehensive genomic profiling analysis to explore differences between male and female patients within a cohort of 195 Taiwanese HCC patients. We did not detect any sex-biased genomic alterations. However, when our investigation extended to the TCGA dataset, we found higher frequencies of gene copy gains in CCNE2 and mutations in CTNNB1 and TP53 among male patients. Besides, we further evaluated the associations between genomic alterations and patients' prognosis by sex. The results showed that female patients harboring tumors with STAT3 gain and alterations in the JAK-STAT pathway displayed a poor prognosis. These two factors remained independently associated with unfavorable prognosis even after adjusting for the patient's age and stage characteristics (Hazard ratio = 10.434, 95% CI 3.331-32.677, P < 0.001; Hazard ratio = 2.547, 95% CI 1.195-5.432, P = 0.016, respectively). In summary, this study provides valuable insights into understanding sex disparity in HCC in the East Asian population. Validation through larger cohorts and extensive sequencing efforts is warranted.

Tissue-specific thresholds of mutation burden associated with anti-PD-1/L1 therapy benefit and prognosis in microsatellite-stable cancers

Immune checkpoint inhibitors (ICIs) targeting programmed cell death protein 1 or its ligand (PD-1/L1) have expanded the treatment landscape against cancers but are effective in only a subset of patients. Tumor mutation burden (TMB) is postulated to be a generic determinant of ICI-dependent tumor rejection. Here we describe the association between TMB and survival outcomes among microsatellite-stable cancers in a real-world clinicogenomic cohort consisting of 70,698 patients distributed across 27 histologies. TMB was associated with survival benefit or detriment depending on tissue and treatment context, with eight cancer types demonstrating a specific association between TMB and improved outcomes upon treatment with anti-PD-1/L1 therapies. Survival benefits were noted over a broad range of TMB cutoffs across cancer types, and a dose-dependent relationship between TMB and outcomes was observed in a subset of cancers. These results have implications for the use of cancer-agnostic and universal TMB cutoffs to guide the use of anti-PD-1/L1 therapies, and they underline the importance of tissue context in the development of ICI biomarkers.

Immunotherapy for endometrial cancer

Advanced recurrent endometrial cancer (EC) has a poor prognosis and new treatment options are needed. In 2013, EC was classified by genomic analysis into four groups: the POLE ultra-mutated group, the MSI-high hypermutated group (MSI-H), the copy number low group, and the copy number high group. The prognosis differs based on the classification, which should enable the individualization of treatment. The MSI-H and POLE types can induce PD-L1 expression in cancer cells. Among the gynecological cancers, EC exhibits the highest levels of PD-1 and PD-L1 expression and has the highest proportion of MSI-H. Thus, an immune checkpoint inhibitor (ICI) is expected to be effective. The first ICI to show efficacy in recurrent EC was the anti-PD1 antibody pembrolizumab, which exhibited efficacy in MSI-H EC. The combination of pembrolizumab and the multi-kinase inhibitor lenvatinib significantly prolongs OS/PFS compared with single-agent chemotherapy in previously treated recurrent EC, regardless of MSI status. ICIs are now moving from second-line and beyond to first-line treatment regimens. The efficacy of paclitaxel plus carboplatin (TC) and ICI combinations compared with TC have been demonstrated, including an ongoing Phase III trial comparing chemotherapy with the combination of pembrolizumab and lenvatinib. Although ICIs are becoming the mainstay of EC, they cause systemic inflammatory side effects known as irAEs. The incidence of irAEs is higher for combination therapy with CT or lenvatinib compared with ICI therapy alone. Even though they are rarely fatal, irAEs should be addressed promptly.

Assessment of TP53 and CDKN2A status as predictive markers of malignant transformation of sinonasal inverted papilloma

The mechanism and predictive biomarkers of sinonasal inverted papilloma (IP) transformation into squamous cell carcinoma (SCC) are still unclear. We investigated the genetic mutations involved and the predictive biomarkers. Fourteen patients with SCC arising from IP and six patients with IPs without malignant transformation (sIP) were included. DNA was extracted separately from areas of normal tissue, IP, dysplasia, and SCC. Whole exome sequencing and immunohistochemistry was performed. Major oncogenic mutations were observed in the progression from IP to SCC. The most frequently mutated genes were TP53 (39%) and CDKN2A (27%). Mutations in TP53 and/or CDKN2A were observed in three of six IPs with malignant transformation (cIP); none were observed in sIPs. Tumor mutational burden (TMB) increased from IP to SCC (0.64/Mb, 1.11/Mb, and 1.25 for IP, dysplasia, and SCC, respectively). TMB was higher in the cIPs than in the sIPs (0.64/Mb vs 0.3/Mb). Three cIPs showed a diffuse strong or null pattern in p53, and one showed a total loss of p16, a distinct pattern from sIPs. Our result suggests that TP53 and CDKN2A status can be predictive markers of malignant transformation of IP. Furthermore, immunohistochemistry of p53 and p16 expression can be surrogate markers for TP53 and CDKN2A status.

Biomarkers in breast cancer 2024: an updated consensus statement by the Spanish Society of Medical Oncology and the Spanish Society of Pathology

This revised consensus statement of the Spanish Society of Medical Oncology (SEOM) and the Spanish Society of Pathological Anatomy (SEAP) updates the recommendations for biomarkers use in the diagnosis and treatment of breast cancer that we first published in 2018. The expert group recommends determining in early breast cancer the estrogen receptor (ER), progesterone receptor (PR), Ki-67, and Human Epidermal growth factor Receptor 2 (HER2), as well as BReast CAncer (BRCA) genes in high-risk HER2-negative breast cancer, to assist prognosis and help in indicating the therapeutic options, including hormone therapy, chemotherapy, anti-HER2 therapy, and other targeted therapies. One of the four available genetic prognostic platforms (Oncotype DX®, MammaPrint®, Prosigna®, or EndoPredict®) may be used in ER-positive patients with early breast cancer to establish a prognostic category and help decide with the patient whether adjuvant treatment may be limited to hormonal therapy. In second-line advanced breast cancer, in addition, phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA) and estrogen receptor 1 (ESR1) should be tested in hormone-sensitive cases, BRCA gene mutations in HER2-negative cancers, and in triple-negative breast cancer (TNBC), programmed cell death-1 ligand (PD-L1). Newer biomarkers and technologies, including tumor-infiltrating lymphocytes (TILs), homologous recombination deficiency (HRD) testing, serine/threonine kinase (AKT) pathway activation, and next-generation sequencing (NGS), are at this point investigational.

Gastroenteropancreatic neuroendocrine neoplasms: current development, challenges, and clinical perspectives

Neuroendocrine neoplasms (NENs) are highly heterogeneous and potentially malignant tumors arising from secretory cells of the neuroendocrine system. Gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) are the most common subtype of NENs. Historically, GEP-NENs have been regarded as infrequent and slow-growing malignancies; however, recent data have demonstrated that the worldwide prevalence and incidence of GEP-NENs have increased exponentially over the last three decades. In addition, an increasing number of studies have proven that GEP-NENs result in a limited life expectancy. These findings suggested that the natural biology of GEP-NENs is more aggressive than commonly assumed. Therefore, there is an urgent need for advanced researches focusing on the diagnosis and management of patients with GEP-NENs. In this review, we have summarized the limitations and recent advancements in our comprehension of the epidemiology, clinical presentations, pathology, molecular biology, diagnosis, and treatment of GEP-NETs to identify factors contributing to delays in diagnosis and timely treatment of these patients.

Spatial Architecture of Myeloid and T Cells Orchestrates Immune Evasion and Clinical Outcome in Lung Cancer

Understanding the role of the tumor microenvironment (TME) in lung cancer is critical to improving patient outcomes. We identified four histology-independent archetype TMEs in treatment-naïve early-stage lung cancer using imaging mass cytometry in the TRACERx study (n = 81 patients/198 samples/2.3 million cells). In immune-hot adenocarcinomas, spatial niches of T cells and macrophages increased with clonal neoantigen burden, whereas such an increase was observed for niches of plasma and B cells in immune-excluded squamous cell carcinomas (LUSC). Immune-low TMEs were associated with fibroblast barriers to immune infiltration. The fourth archetype, characterized by sparse lymphocytes and high tumor-associated neutrophil (TAN) infiltration, had tumor cells spatially separated from vasculature and exhibited low spatial intratumor heterogeneity. TAN-high LUSC had frequent PIK3CA mutations. TAN-high tumors harbored recently expanded and metastasis-seeding subclones and had a shorter disease-free survival independent of stage. These findings delineate genomic, immune, and physical barriers to immune surveillance and implicate neutrophil-rich TMEs in metastasis.

SIGNIFICANCE

This study provides novel insights into the spatial organization of the lung cancer TME in the context of tumor immunogenicity, tumor heterogeneity, and cancer evolution. Pairing the tumor evolutionary history with the spatially resolved TME suggests mechanistic hypotheses for tumor progression and metastasis with implications for patient outcome and treatment. This article is featured in Selected Articles from This Issue, p. 897.

Comprehensive genomic profiling and therapeutic implications for Taiwanese patients with treatment-naïve breast cancer

BACKGROUND

Breast cancer is a heterogeneous disease categorized based on molecular characteristics, including hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) expression levels. The emergence of profiling technology has revealed multiple driver genomic alterations within each breast cancer subtype, serving as biomarkers to predict treatment outcomes. This study aimed to explore the genomic landscape of breast cancer in the Taiwanese population through comprehensive genomic profiling (CGP) and identify diagnostic and predictive biomarkers.

METHODS

Targeted next-generation sequencing-based CGP was performed on 116 archived Taiwanese breast cancer specimens, assessing genomic alterations (GAs), including single nucleotide variants, copy number variants, fusion genes, tumor mutation burden (TMB), and microsatellite instability (MSI) status. Predictive variants for FDA-approved therapies were evaluated within each subtype.

RESULTS

In the cohort, frequent mutations included PIK3CA (39.7%), TP53 (36.2%), KMT2C (9.5%), GATA3 (8.6%), and SF3B1 (6.9%). All subtypes had low TMB, with no MSI-H tumors. Among HR + HER2- patients, 42% (27/65) harbored activating PIK3CA mutations, implying potential sensitivity to PI3K inhibitors and resistance to endocrine therapies. HR + HER2- patients exhibited intrinsic hormonal resistance via FGFR1 gene gain/amplification (15%), exclusive of PI3K/AKT pathway alterations. Aberrations in the PI3K/AKT/mTOR and FGFR pathways were implicated in chemoresistance, with a 52.9% involvement in triple-negative breast cancer. In HER2+ tumors, 50% harbored GAs potentially conferring resistance to anti-HER2 therapies, including PIK3CA mutations (32%), MAP3K1 (2.9%), NF1 (2.9%), and copy number gain/amplification of FGFR1 (18%), FGFR3 (2.9%), EGFR (2.9%), and AKT2 (2.9%).

CONCLUSION

This study presents CGP findings for treatment-naïve Taiwanese breast cancer, emphasizing its value in routine breast cancer management, disease classification, and treatment selection.

Immunotherapy combination approaches: mechanisms, biomarkers and clinical observations

The approval of the first immune checkpoint inhibitors provided a paradigm shift for the treatment of malignancies across a broad range of indications. Whereas initially, single-agent immune checkpoint inhibition was used, increasing numbers of patients are now treated with combination immune checkpoint blockade, where non-redundant mechanisms of action of the individual agents generally lead to higher response rates. Furthermore, immune checkpoint therapy has been combined with various other therapeutic modalities, including chemotherapy, radiotherapy and other immunotherapeutics such as vaccines, adoptive cellular therapies, cytokines and others, in an effort to maximize clinical efficacy. Currently, a large number of clinical trials test combination therapies with an immune checkpoint inhibitor as a backbone. However, proceeding without inclusion of broad, if initially exploratory, biomarker investigations may ultimately slow progress, as so far, few combinations have yielded clinical successes based on clinical data alone. Here, we present the rationale for combination therapies and discuss clinical data from clinical trials across the immuno-oncology spectrum. Moreover, we discuss the evolution of biomarker approaches and highlight the potential new directions that comprehensive biomarker studies can yield.

Construction and analysis of a reliable five-gene prognostic signature for colon adenocarcinoma associated with the wild-type allelic state of the COL6A6 gene

Background

Tumors emerge by acquiring a number of mutations over time. The first mutation provides a selective growth advantage compared to adjacent epithelial cells, allowing the cell to create a clone that can outgrow the cells that surround it. Subsequent mutations determine the risk of the tumor progressing to metastatic cancer. Some secondary mutations may inhibit the aggressiveness of the tumor while still increasing the survival of the clone. Meaningful mutations in genes may provide a strong molecular foundation for developing novel therapeutic strategies for cancer.

Methods

The somatic mutation and prognosis in colon adenocarcinoma (COAD) were analyzed. The copy number variation (CNV) and differentially expressed genes (DEGs) between the collagen type VI alpha 6 chain (COL6A6) mutation (COL6A6-MUT) and the COL6A6 wild-type (COL6A6-WT) subgroups were evaluated. The independent prognostic signatures based on COL6A6-allelic state were determined to construct a Cox model. The biological characteristics and the immune microenvironment between the two risk groups were compared.

Results

COL6A6 was found to be highly mutated in COAD at a frequency of 9%. Patients with COL6A6-MUT had a good overall survival (OS) compared to those with COL6A6-WT, who had a different CNV pattern. Significant differences in gene expression were established for 593 genes between the COL6A6-MUT and COL6A6-WT samples. Among them, MUC16, ASNSP1, PRR18, PEG10, and RPL26P8 were determined to be independent prognostic factors. The internally validated prognostic risk model, constructed using these five genes, demonstrated its value by revealing a significant difference in patient prognosis between the high-risk and low-risk groups. Specifically, patients in the high-risk group exhibited a considerably worse prognosis than did those in the low-risk group. The high-risk group had a significantly higher proportion of patients over 60 years of age and patients in stage III. Moreover, the tumor immune dysfunction and exclusion (TIDE) score and the expression of human leukocyte antigen (HLA) family genes were all higher in the high-risk group than that in the low-risk group.

Conclusions

The allelic state of COL6A6 and the five associated DEGs were identified as novel biomarkers for the diagnosis and prognosis of COAD and may be therapeutic targets in COAD.

Comparison of target agent treatment strategies for platinum-resistant recurrent ovarian cancer: A Bayesian network meta-analysis

BACKGROUND

We aimed to compare 7 newer immunotherapies and targeted therapies for platinum-resistant relapsed ovarian cancer.

METHODS

We conducted a comprehensive search of PubMed, EMBASE, and Cochrane Library electronic databases for phase III trials involving platinum-resistant recurrent ovarian cancer (PRrOC) patients treated with immunotherapy or targeted therapy in combination with chemotherapy. The quality of the included trials was assessed using the GRADE method. The primary outcome of comparison was progression-free survival, and secondary outcomes included overall survival and safety.

RESULTS

This analysis included 7 randomized phase III controlled trials, encompassing 2485 PRrOC patients. Combining bevacizumab plus chemotherapy and lurbinectedin demonstrated statistically significant differences in progression-free survival compared to all other regimens of interest. However, no statistically significant differences were observed in the overall survival. Nivolumab and mirvetuximab exhibited fewer serious adverse events than the other regimens of interest.

CONCLUSIONS

Our findings indicate that bevacizumab combined with chemotherapy and lurbinectedin monotherapy has significant efficacy in patients with PRrOC. For patients with PRrOC who have exhausted treatment options, nivolumab and mirvetuximab may be considered as alternatives because of their better safety profiles.

Harmonizing tumor mutational burden analysis: Insights from a multicenter study using in silico reference data sets in clinical whole-exome sequencing (WES)

OBJECTIVES

Tumor mutational burden (TMB) is a significant biomarker for predicting immune checkpoint inhibitor response, but the clinical performance of whole-exome sequencing (WES)-based TMB estimation has received less attention compared to panel-based methods. This study aimed to assess the reliability and comparability of WES-based TMB analysis among laboratories under routine testing conditions.

METHODS

A multicenter study was conducted involving 24 laboratories in China using in silico reference data sets. The accuracy and comparability of TMB estimation were evaluated using matched tumor-normal data sets. Factors such as accuracy of variant calls, limit of detection (LOD) of WES test, size of regions of interest (ROIs) used for TMB calculation, and TMB cutoff points were analyzed.

RESULTS

The laboratories consistently underestimated the expected TMB scores in matched tumor-normal samples, with only 50% falling within the ±30% TMB interval. Samples with low TMB score (<2.5) received the consensus interpretation. Accuracy of variant calls, LOD of the WES test, ROI, and TMB cutoff points were important factors causing interlaboratory deviations.

CONCLUSIONS

This study highlights real-world challenges in WES-based TMB analysis that need to be improved and optimized. This research will aid in the selection of more reasonable analytical procedures to minimize potential methodologic biases in estimating TMB in clinical exome sequencing tests. Harmonizing TMB estimation in clinical testing conditions is crucial for accurately evaluating patients' response to immunotherapy.

Comprehensive molecular profiling identifies actionable biomarkers for patients from Thailand and the United Arab Emirates with advanced malignancies

Background

Comprehensive molecular profiling of tissue samples that can help guide therapy management is not widely available across the globe.

Methods

Comprehensive molecular profiling through Caris Molecular Intelligence involves the analysis of DNA through next-generation sequencing, chromogenic or fluorescent in situ hybridization, pyrosequencing, and copy number alterations; RNA through whole-transcriptome sequencing and multiplex PCR of RNA; and protein through immunohistochemistry.

Results

Here we describe the experience of molecular profiling of tumor tissue samples from patients diagnosed with advanced solid tumors and treated in two countries, the United Arab Emirates and Thailand. Tumor cancer cases submitted to Caris Life Sciences (Phoenix, Arizona, USA) for molecular profiling from the UAE and Thailand were retrospectively analyzed (data accessed between 2019 and 2020) for their molecular alterations and clinical biomarkers, without regard to ethnicity. A total of 451 samples from 35 distinct types of advanced cancers were examined for mutations, amplifications, overexpression, exon copy number alterations, microsatellite instability, deficient mismatch repair, tumor mutational burden, and fusions. Interrogating each step of the biological pathway, from DNA to RNA to distinct protein, identified an alteration with an associated therapy for 75% of these tumor samples. The most common alterations identified included elevated PDL-1 that can be targeted with an immune checkpoint inhibitors and amplification of HER2 for which a variety of anti HER2 therapies are available.

Conclusion

Comprehensive molecular profiling in patients with advanced malignancies can help optimize therapeutic management allowing for improved prognostic outcome.

Differential Responses to Immune Checkpoint Inhibitors are Governed by Diverse Mismatch Repair Gene Alterations

PURPOSE

The response to immune checkpoint inhibitors (ICI) in deficient mismatch repair (dMMR) colorectal cancer and endometrial cancer is variable. Here, we explored the differential response to ICIs according to different mismatch repair alterations.

EXPERIMENTAL DESIGN

Colorectal cancer (N = 13,701) and endometrial cancer (N = 3,315) specimens were tested at Caris Life Sciences. Median overall survival (mOS) was estimated using Kaplan-Meier. The prediction of high-, intermediate-, and low-affinity epitopes by tumor mutation burden (TMB) values was conducted using R-squared (R2).

RESULTS

Compared with mutL (MLH1 and PMS2) co-loss, the mOS was longer in mutS (MSH2 and MSH6) co-loss in all colorectal cancer (54.6 vs. 36 months; P = 0.0.025) and endometrial cancer (81.5 vs. 48.2 months; P < 0.001) patients. In ICI-treated patients, the mOS was longer in mutS co-loss in colorectal cancer [not reached (NR) vs. 36 months; P = 0.011). In endometrial cancer, the mOS was NR vs. 42.2 months; P = 0.711]. The neoantigen load (NAL) in mutS co-loss compared with mutL co-loss was higher in colorectal cancer (high-affinity epitopes: 25.5 vs. 19; q = 0.017, intermediate: 39 vs. 32; q = 0.004, low: 87.5 vs. 73; q < 0.001) and endometrial cancer (high-affinity epitopes: 15 vs. 11; q = 0.002, intermediate: 27.5 vs. 19; q < 0.001, low: 59 vs. 41; q < 0.001), respectively. R2 ranged from 0.25 in mutS co-loss colorectal cancer to 0.95 in mutL co-loss endometrial cancer.

CONCLUSIONS

Patients with mutS co-loss experienced longer mOS in colorectal cancer and endometrial cancer and better response to ICIs in colorectal cancer. Among all explored biomarkers, NAL was higher in mutS co-loss and may be a potential driving factor for the observed better outcomes. TMB did not reliably predict NAL.

Large-Scale Cancer Genomic Analysis Reveals Significant Disparities between Microsatellite Instability and Tumor Mutational Burden

BACKGROUND

Microsatellite instability (MSI) and tumor mutational burden (TMB) are predictive biomarkers for pan-cancer immunotherapy. The interrelationship between MSI-high (MSI-H) and TMB-high (TMB-H) in human cancers and their predictive value for immunotherapy in lung cancer remain unclear.

METHODS

We analyzed somatic mutation data from the Genomics Evidence Neoplasia Information Exchange (n = 46,320) to determine the relationship between MSI-H and TMB-H in human cancers using adjusted multivariate regression models. Patient survival was examined using the Cox proportional hazards model. The association between MSI and genetic mutations was assessed.

RESULTS

Patients (31-89%) with MSI-H had TMB-low phenotypes across 22 cancer types. Colorectal and stomach cancers showed the strongest association between TMB and MSI. TMB-H patients with lung cancer who received immunotherapy exhibited significantly higher overall survival [HR, 0.61; 95% confidence interval (CI), 0.44-0.86] and progression-free survival (HR, 0.65; 95% CI, 0.47-0.91) compared to the TMB-low group; no significant benefit was observed in the MSI-H group. Patients with TMB and MSI phenotypes showed further improvement in overall survival and PFS. We identified several mutated genes associated with MSI-H phenotypes, including known mismatch repair genes and novel mutated genes, such as ARID1A and ARID1B.

CONCLUSIONS

Our results demonstrate that TMB-H and/or a combination of MSI-H can serve as biomarkers for immunotherapies in lung cancer.

IMPACT

These findings suggest that distinct or combined biomarkers should be considered for immunotherapy in human cancers because notable discrepancies exist between MSI-H and TMB-H across different cancer types.

Tumor mutational burden in colorectal cancer: Implications for treatment

Although immune checkpoint inhibitors have revolutionized the treatment of several advanced solid cancers, in colorectal cancer, the transformative benefit of these innovative medicines is currently limited to those with deficient mismatch repair or high microsatellite instability. Tumor mutational burden (TMB) has emerged as a potential predictor of immunotherapy benefit, but the lack of standardization in its assessment and reporting has hindered the introduction of this biomarker in routine clinical practice. Here, we compiled 45 colorectal cancer studies utilizing numerical thresholds for high-TMB. In this group of studies, TMB cut-offs ranged from 6.88 to 41 mut/Mb and were most often set at 10, 17, or 20 mut/Mb. Additionally, we observed divergent TMB definitions and inconsistent disclosure of specific methodological details, which collectively emphasize the substantial lack of harmonization within the field. Ongoing efforts to harmonize TMB assessment will be critical to validate TMB as a predictive marker of immunotherapy response.

Comprehensive analysis and prognostic assessment of senescence-associated genes in bladder cancer

BACKGROUND

The prevalence and mortality of bladder cancer (BLCA) present a significant medical challenge. While the function of senescence-related genes in tumor development is recognized, their prognostic significance in BLCA has not been thoroughly explored.

METHODS

BLCA transcriptome datasets were sourced from the TCGA and GEO repositories. Gene groupings were determined through differential gene expression and non-negative matrix factorization (NMF) methodologies. Key senescence-linked genes were isolated using singular and multivariate Cox regression analyses, combined with lasso regression. Validation was undertaken with GEO database information. Predictive models, or nomograms, were developed by merging risk metrics with clinical records, and their efficacy was gauged using ROC curve methodologies. The immune response's dependency on the risk metric was assessed through the immune phenomenon score (IPS). Additionally, we estimated IC50 metrics for potential chemotherapeutic agents.

RESULTS

Reviewing 406 neoplastic and 19 standard tissue specimens from the TCGA repository facilitated the bifurcation of subjects into two unique clusters (C1 and C2) according to senescence-related gene expression. After a stringent statistical evaluation, a set of ten pivotal genes was discerned and applied for risk stratification. Validity tests for the devised nomograms in forecasting 1, 3, and 5-year survival probabilities for BLCA patients were executed via ROC and calibration plots. IC50 estimations highlighted a heightened responsiveness in the low-risk category to agents like cisplatin, cyclopamine, and sorafenib.

CONCLUSIONS

In summation, our research emphasizes the prospective utility of risk assessments rooted in senescence-related gene signatures for enhancing BLCA clinical oversight.

The Genomic, Transcriptomic, and Immunologic Landscape of HRAS Mutations in Solid Tumors

Tipifarnib is the only targeted therapy breakthrough for HRAS-mutant (HRASmt) recurrent or metastatic head and neck squamous cell carcinoma (HNSCC). The molecular profiles of HRASmt cancers are difficult to explore given the low frequency of HRASmt. This study aims to understand the molecular co-alterations, immune profiles, and clinical outcomes of 524 HRASmt solid tumors including urothelial carcinoma (UC), breast cancer (BC), non-small-cell lung cancer (NSCLC), melanoma, and HNSCC. HRASmt was most common in UC (3.0%), followed by HNSCC (2.82%), melanoma (1.05%), BC (0.45%), and NSCLC (0.44%). HRASmt was absent in Her2+ BC regardless of hormone receptor status. HRASmt was more frequently associated with squamous compared to non-squamous NSCLC (60% vs. 40% in HRASwt, p = 0.002). The tumor microenvironment (TME) of HRASmt demonstrated increased M1 macrophages in triple-negative BC (TNBC), HNSCC, squamous NSCLC, and UC; increased M2 macrophages in TNBC; and increased CD8+ T-cells in HNSCC (all p < 0.05). Finally, HRASmt was associated with shorter overall survival in HNSCC (HR: 1.564, CI: 1.16-2.11, p = 0.003) but not in the other cancer types examined. In conclusion, this study provides new insights into the unique molecular profiles of HRASmt tumors that may help to identify new targets and guide future clinical trial design.

A novel tumor mutation-related long non-coding RNA signature for predicting overall survival and immunotherapy response in lung adenocarcinoma

Background

Immunotherapy has changed the treatment landscape for lung cancer. This study aims to construct a tumor mutation-related model that combines long non-coding RNA (lncRNA) expression levels and tumor mutation levels in tumor genomes to detect the possibilities of the lncRNA signature as an indicator for predicting the prognosis and response to immunotherapy in lung adenocarcinoma (LUAD).

Methods

We downloaded the tumor mutation profiles and RNA-seq expression database of LUAD from The Cancer Genome Atlas (TCGA). Differentially expressed lncRNAs were extracted based on the cumulative number of mutations. Cox regression analyses were used to identify the prognostic lncRNA signature, and the prognostic value of the five selected lncRNAs was validated by using survival analysis and the receiver operating characteristic (ROC) curve. We used qPCR to validate the expression of five selected lncRNAs between human lung epithelial and human lung adenocarcinoma cell lines. The ImmuCellAI, immunophenoscore (IPS) scores and Tumor Immune Dysfunction and Exclusion (TIDE) analyses were used to predict the response to immunotherapy for this mutation related lncRNA signature.

Results

A total of 162 lncRNAs were detected among the differentially expressed lncRNAs between the Tumor mutational burden (TMB)-high group and the TMB-low group. Then, five lncRNAs (PLAC4, LINC01116, LINC02163, MIR223HG, FAM83A-AS1) were identified as tumor mutation-related candidates for constructing the prognostic prediction model. Kaplan‒Meier curves showed that the overall survival of the low-risk group was significantly better than that of the high-risk group, and the results of the GSE50081 set were consistent. The expression levels of PD1, PD-L1 and CTLA4 in the low-risk group were higher than those in the high-risk group. The IPS scores and TIDE scores of patients in the low-risk group were significantly higher than those in the high-risk group.

Conclusion

Our findings demonstrated that the five lncRNAs (PLAC4, LINC01116, LINC02163, MIR223HG, FAM83A-AS1) were identified as candidates for constructing the tumor mutation-related model which may serve as an indicator of tumor mutation levels and have important implications for predicting the response to immunotherapy in LUAD.

Machine learning-based identification of a consensus immune-derived gene signature to improve head and neck squamous cell carcinoma therapy and outcome

Background

Head and neck squamous cell carcinoma (HNSCC), an extremely aggressive tumor, is often associated with poor outcomes. The standard anatomy-based tumor-node-metastasis staging system does not satisfy the requirements for screening treatment-sensitive patients. Thus, an ideal biomarker leading to precise screening and treatment of HNSCC is urgently needed.

Methods

Ten machine learning algorithms-Lasso, Ridge, stepwise Cox, CoxBoost, elastic network (Enet), partial least squares regression for Cox (plsRcox), random survival forest (RSF), generalized boosted regression modelling (GBM), supervised principal components (SuperPC), and survival support vector machine (survival-SVM)-as well as 85 algorithm combinations were applied to construct and identify a consensus immune-derived gene signature (CIDGS).

Results

Based on the expression profiles of three cohorts comprising 719 patients with HNSCC, we identified 236 consensus prognostic genes, which were then filtered into a CIDGS, using the 10 machine learning algorithms and 85 algorithm combinations. The results of a study involving a training cohort, two testing cohorts, and a meta-cohort consistently demonstrated that CIDGS was capable of accurately predicting prognoses for HNSCC. Incorporation of several core clinical features and 51 previously reported signatures, enhanced the predictive capacity of the CIDGS to a level which was markedly superior to that of other signatures. Notably, patients with low CIDGS displayed fewer genomic alterations and higher immune cell infiltrate levels, as well as increased sensitivity to immunotherapy and other therapeutic agents, in addition to receiving better prognoses. The survival times of HNSCC patients with high CIDGS, in particular, were shorter. Moreover, CIDGS enabled accurate stratification of the response to immunotherapy and prognoses for bladder cancer. Niclosamide and ruxolitinib showed potential as therapeutic agents in HNSCC patients with high CIDGS.

Conclusion

CIDGS may be used for stratifying risks as well as for predicting the outcome of patients with HNSCC in a clinical setting.

Comparative molecular profiling of pancreatic ductal adenocarcinoma of the head versus body and tail

Pancreatic ductal adenocarcinoma (PDAC) of the head (H) and body/tail (B/T) differ in embryonic origin, cell composition, blood supply, lymphatic and venous drainage, and innervation. We aimed to compare the molecular and tumor immune microenvironment (TIME) profiles of PDAC of the H vs. B/T. A total of 3499 PDAC samples were analyzed via next-generation sequencing (NGS) of RNA (whole transcriptome, NovaSeq), DNA (NextSeq, 592 genes or NovaSeq, whole exome sequencing), and immunohistochemistry (Caris Life Sciences, Phoenix, AZ). Significance was determined as p values adjusted for multiple corrections (q) of <0.05. Anatomic subsites of PDAC tumors were grouped by primary tumor sites into H (N = 2058) or B/T (N = 1384). There were significantly more metastatic tumors profiled from B/T vs. H (57% vs. 44%, p < 0.001). KRAS mutations (93.8% vs. 90.2%), genomic loss of heterozygosity (12.7% vs. 9.1%), and several copy number alterations (FGF3, FGF4, FGF19, CCND1, ZNF703, FLT4, MUTYH, TNFRS14) trended higher in B/T when compared to H (p < 0.05 but q > 0.05). Expression analysis of immuno-oncology (IO)-related genes showed significantly higher expression of CTLA4 and PDCD1 in H (q < 0.05, fold change 1.2 and 1.3) and IDO1 and PDCD1LG2 expression trended higher in B/T (p < 0.05, fold change 0.95). To our knowledge, this is one of the largest cohorts of PDAC tumors subjected to broad molecular profiling. Differences in IO-related gene expression and TIME cell distribution suggest that response to IO therapies may differ in PDAC arising from H vs. B/T. Subtle differences in the genomic profiles of H vs. B/T tumors were observed.

A paradigm shift in cancer research based on integrative multi-omics approaches: glutaminase serves as a pioneering cuproptosis-related gene in pan-cancer

BACKGROUND

Cuproptosis is a newly identified form of unprogrammed cell death. As a pivotal metabolic regulator, glutaminase (GLS) has recently been discovered to be linked to cuproptosis. Despite this discovery, the oncogenic functions and mechanisms of GLS in various cancers are still not fully understood.

METHODS

In this study, a comprehensive omics analysis was performed to investigate the differential expression levels, diagnostic and prognostic potential, correlation with tumor immune infiltration, genetic alterations, and drug sensitivity of GLS across multiple malignancies.

RESULTS

Our findings revealed unique expression patterns of GLS across various cancer types and molecular subtypes of carcinomas, underscoring its pivotal role primarily in energy and nutrition metabolism. Additionally, GLS showed remarkable diagnostic and prognostic performance in specific cancers, suggesting its potential as a promising biomarker for cancer detection and prognosis. Furthermore, we focused on uterine corpus endometrial carcinoma (UCEC) and developed a novel prognostic model associated with GLS, indicating a close correlation between GLS and UCEC. Moreover, our exploration into immune infiltration, genetic heterogeneity, tumor stemness, and drug sensitivity provided novel insights and directions for future research and laid the foundation for high-quality verification.

CONCLUSION

Collectively, our study is the first comprehensive investigation of the biological and clinical significance of GLS in pan-cancer. In our study, GLS was identified as a promising biomarker for UCEC, providing valuable evidence and a potential target for anti-tumor therapy. Overall, our findings shed light on the multifaceted functions of GLS in cancer and offer new avenues for further research.

Exploring the Cost Effectiveness of a Whole-Genome Sequencing-Based Biomarker for Treatment Selection in Patients with Advanced Lung Cancer Ineligible for Targeted Therapy

OBJECTIVE

We aimed to perform an early cost-effectiveness analysis of using a whole-genome sequencing-based tumor mutation burden (WGS-TMB), instead of programmed death-ligand 1 (PD-L1), for immunotherapy treatment selection in patients with non-squamous advanced/metastatic non-small cell lung cancer ineligible for targeted therapy, from a Dutch healthcare perspective.

METHODS

A decision-model simulating individual patients with metastatic non-small cell lung cancer was used to evaluate diagnostic strategies to select first-line immunotherapy only or the immunotherapy plus chemotherapy combination. Treatment was selected using PD-L1 [A, current practice], WGS-TMB [B], and both PD-L1 and WGS-TMB [C]. Strategies D, E, and F take into account a patient's disease burden, in addition to PD-L1, WGS-TMB, and both PD-L1 and WGS-TMB, respectively. Disease burden was defined as a fast-growing tumor, a high number of metastases, and/or weight loss. A threshold of 10 mutations per mega-base was used to classify patients into TMB-high and TMB-low groups. Outcomes were discounted quality-adjusted life-years (QALYs) and healthcare costs measured from the start of first-line treatment to death. Healthcare costs includes drug acquisition, follow-up costs, and molecular diagnostic tests (i.e., standard diagnostic techniques and/or WGS for strategies involving TMB). Results were reported using the net monetary benefit at a willingness-to-pay threshold of €80,000/QALY. Additional scenario and threshold analyses were performed.

RESULTS

Strategy B had the lowest QALYs (1.84) and lowest healthcare costs (€120,800). The highest QALYs and healthcare costs were 2.00 and €140,400 in strategy F. In the base-case analysis, strategy A was cost effective with the highest net monetary benefit (€27,300), followed by strategy B (€26,700). Strategy B was cost effective when the cost of WGS testing was decreased by at least 24% or when immunotherapy results in an additional 0.5 year of life gained or more for TMB high compared with TMB low. Strategies C and F, which combined TMB and PD-L1 had the highest net monetary benefit (≥ €76,900) when the cost of WGS testing, immunotherapy, and chemotherapy acquisition were simultaneously reduced by at least 47%, 39%, and 43%, respectively. Furthermore, strategy C resulted in the highest net monetary benefit (≥ €39,900) in a scenario where patients with both PD-L1 low and TMB low were treated with chemotherapy instead of immunotherapy plus chemotherapy.

CONCLUSIONS

The use of WGS-TMB is not cost effective compared to PD-L1 for immunotherapy treatment selection in non-squamous metastatic non-small cell lung cancer in the Netherlands. WGS-TMB could become cost effective provided there is a reduction in the cost of WGS testing or there is an increase in the predictive value of WGS-TMB for immunotherapy effectiveness. Alternatively, a combination strategy of PD-L1 testing with WGS-TMB would be cost effective if used to support the choice to withhold immunotherapy in patients with a low expected benefit of immunotherapy.

Personalizing Oncolytic Immunovirotherapy Approaches

Development of successful cancer therapeutics requires exploration of the differences in genetics, metabolism, and interactions with the immune system among malignant and normal cells. The clinical observation of spontaneous tumor regression following natural infection with microorganism has created the premise of their use as cancer therapeutics. Oncolytic viruses (OVs) originate from viruses with attenuated virulence in humans, well-characterized vaccine strains of known human pathogens, or engineered replication-deficient viral vectors. Their selectivity is based on receptor expression level and post entry restriction factors that favor replication in the tumor, while keeping the normal cells unharmed. Clinical trials have demonstrated a wide range of patient responses to virotherapy, with subgroups of patients significantly benefiting from OV administration. Tumor-specific gene signatures, including antiviral interferon-stimulated gene (ISG) expression profile, have demonstrated a strong correlation with tumor permissiveness to infection. Furthermore, the combination of OVs with immunotherapeutics, including anticancer vaccines and immune checkpoint inhibitors [ICIs, such as anti-PD-1/PD-L1 or anti-CTLA-4 and chimeric antigen receptor (CAR)-T or CAR-NK cells], could synergistically improve the therapeutic outcome. Creating response prediction algorithms represents an important step for the transition to individualized immunovirotherapy approaches in the clinic. Integrative predictors could include tumor mutational burden (TMB), inflammatory gene signature, phenotype of tumor-infiltrating lymphocytes, tumor microenvironment (TME), and immune checkpoint receptor expression on both immune and target cells. Additionally, the gut microbiota has recently been recognized as a systemic immunomodulatory factor and could further be used in the optimization of individualized immunovirotherapy algorithms.

Tumor mutational burden assessment and standardized bioinformatics approach using custom NGS panels in clinical routine

BACKGROUND

High tumor mutational burden (TMB) was reported to predict the efficacy of immune checkpoint inhibitors (ICIs). Pembrolizumab, an anti-PD-1, received FDA-approval for the treatment of unresectable/metastatic tumors with high TMB as determined by the FoundationOne®CDx test. It remains to be determined how TMB can also be calculated using other tests.

RESULTS

FFPE/frozen tumor samples from various origins were sequenced in the frame of the Institut Curie (IC) Molecular Tumor Board using an in-house next-generation sequencing (NGS) panel. A TMB calculation method was developed at IC (IC algorithm) and compared to the FoundationOne® (FO) algorithm. Using IC algorithm, an optimal 10% variant allele frequency (VAF) cut-off was established for TMB evaluation on FFPE samples, compared to 5% on frozen samples. The median TMB score for MSS/POLE WT tumors was 8.8 mut/Mb versus 45 mut/Mb for MSI/POLE-mutated tumors. When focusing on MSS/POLE WT tumor samples, the highest median TMB scores were observed in lymphoma, lung, endometrial, and cervical cancers. After biological manual curation of these cases, 21% of them could be reclassified as MSI/POLE tumors and considered as "true TMB high." Higher TMB values were obtained using FO algorithm on FFPE samples compared to IC algorithm (40 mut/Mb [10-3927] versus 8.2 mut/Mb [2.5-897], p < 0.001).

CONCLUSIONS

We herein propose a TMB calculation method and a bioinformatics tool that is customizable to different NGS panels and sample types. We were not able to retrieve TMB values from FO algorithm using our own algorithm and NGS panel.

Evaluation of Endobronchial Ultrasound-Guided Transbronchial Needle Aspiration (EBUS-TBNA) Samples from Advanced Non-Small Cell Lung Cancer for Whole Genome, Whole Exome and Comprehensive Panel Sequencing

Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) is often the only source of tumor tissue from patients with advanced, inoperable lung cancer. EBUS-TBNA aspirates are used for the diagnosis, staging, and genomic testing to inform therapy options. Here we extracted DNA and RNA from 220 EBUS-TBNA aspirates to evaluate their suitability for whole genome (WGS), whole exome (WES), and comprehensive panel sequencing. For a subset of 40 cases, the same nucleic acid extraction was sequenced using WGS, WES, and the TruSight Oncology 500 assay. Genomic features were compared between sequencing platforms and compared with those reported by clinical testing. A total of 204 aspirates (92.7%) had sufficient DNA (100 ng) for comprehensive panel sequencing, and 109 aspirates (49.5%) had sufficient material for WGS. Comprehensive sequencing platforms detected all seven clinically reported tier 1 actionable mutations, an additional three (7%) tier 1 mutations, six (15%) tier 2-3 mutations, and biomarkers of potential immunotherapy benefit (tumor mutation burden and microsatellite instability). As expected, WGS was more suited for the detection and discovery of emerging novel biomarkers of treatment response. WGS could be performed in half of all EBUS-TBNA aspirates, which points to the enormous potential of EBUS-TBNA as source material for large, well-curated discovery-based studies for novel and more effective predictors of treatment response. Comprehensive panel sequencing is possible in the vast majority of fresh EBUS-TBNA aspirates and enhances the detection of actionable mutations over current clinical testing.

Pan-cancer analysis revealed prognosis value and immunological relevance of RAMPs

Whether receptor activity-modifying proteins (RAMPs) play a key role in human cancer prognosis and immunity remains unknown. We used data from the public databases, The Cancer Genome Atlas, Therapeutically Applicable Research to Generate Effective Treatments, and the Genotype-Tissue Expression project. We utilized bioinformatics methods, R software, and a variety of online databases to analyze RAMPs. In general, RAMPs were significantly and differentially expressed in multiple tumors, and RAMP expression was closely associated with prognosis, immune checkpoints, RNA-editing genes, tumor mutational burden, microsatellite instability, ploidy, and stemness indices. In addition, the expression of RAMPs is strongly correlated with tumor-infiltrating lymphocytes in human cancers. Moreover, the RAMP co-expression network is largely involved in many immune-related biological processes. Quantitative reverse transcription polymerase chain reaction and Western blot proved that RAMP3 was highly expressed in glioma, and RAMP3 promoted tumor proliferation and migration. RAMPs exhibit potential as prognostic and immune-related biomarkers in human cancers. Moreover, RAMPs can be potentially developed as therapeutic targets or used to enhance the efficacy of immunotherapy.

Analytical validation and clinical utilization of K-4CARE™: a comprehensive genomic profiling assay with personalized MRD detection

Background: Biomarker testing has gradually become standard of care in precision oncology to help physicians select optimal treatment for patients. Compared to single-gene or small gene panel testing, comprehensive genomic profiling (CGP) has emerged as a more time- and tissue-efficient method. This study demonstrated in-depth analytical validation of K-4CARE, a CGP assay that integrates circulating tumor DNA (ctDNA) tracking for residual cancer surveillance. Methods: The assay utilized a panel of 473 cancer-relevant genes with a total length of 1.7 Mb. Reference standards were used to evaluate limit of detection (LOD), concordance, sensitivity, specificity and precision of the assay to detect single nucleotide variants (SNVs), small insertion/deletions (Indels), gene amplification and fusion, microsatellite instability (MSI) and tumor mutational burden (TMB). The assay was then benchmarked against orthogonal methods using 155 clinical samples from 10 cancer types. In selected cancers, top tumor-derived somatic mutations, as ranked by our proprietary algorithm, were used to detect ctDNA in the plasma. Results: For detection of somatic SNVs and Indels, gene fusion and amplification, the assay had sensitivity of >99%, 94% and >99% respectively, and specificity of >99%. Detection of germline variants also achieved sensitivity and specificity of >99%. For TMB measurement, the correlation coefficient between whole-exome sequencing and our targeted panel was 97%. MSI analysis when benchmarked against polymerase chain reaction method showed sensitivity of 94% and specificity of >99%. The concordance between our assay and the TruSight Oncology 500 assay for detection of somatic variants, TMB and MSI measurement was 100%, 89%, and 98% respectively. When CGP-informed mutations were used to personalize ctDNA tracking, the detection rate of ctDNA in liquid biopsy was 79%, and clinical utility in cancer surveillance was demonstrated in 2 case studies. Conclusion: K-4CARE™ assay provides comprehensive and reliable genomic information that fulfills all guideline-based biomarker testing for both targeted therapy and immunotherapy. Integration of ctDNA tracking helps clinicians to further monitor treatment response and ultimately provide well-rounded care to cancer patients.

Systematic pan-cancer analyses of the potential function of the Golgi scaffold protein PAQR3

Progesterone and AdipoQ Receptor 3 (PAQR3) is a member of the AdipoQ receptor. Our previous studies have found that PAQR3 plays a role as a candidate inhibitor in cardiac adenocarcinoma, breast cancer, gastric cancer and colorectal cancer, but the systematic analysis of PAQR3 in tumors is currently lacking. The objective of this study was to investigate the prognostic and therapeutic value of PAQR3 in 31 tumors. Through the analysis of TCGA, UALCAN, GEO, GEPIA2, TIMER, Kaplan-Meier plotter, TISIDB and other databases, it was found that the expression level of PAQR3 changed significantly in different tumor types, and the expression level of Neuroblastoma was very high. And the level of Prostate adenocarcinoma is low. In addition, the expression level of PAQR3 in Cholangiocarcinoma, Esophageal carcinoma, Head and neck squamous carcinoma, Liver Hepatocellular Carcinoma, Lung Adenocarcinoma and Lung squamous cell carcinoma was significantly higher than that in normal tissues. However, the expression level of PAQR3 in Breast Cancer, Kidney Renal Clear Cell Carcinoma, Kidney renal papillary cell carcinoma, Prostate Adenocarcinoma, Rectum Adenocarcinoma, Thyroid Cancer and Uterine Corpus Endometrial Carcinoma was lower than that in normal tissues. Subsequently, we explored the value of PAQR3 as a prognostic indicator of cancer. In Acute Myeloid Leukemia, Lower-grade Glioma and Glioblastoma, Pediatric Low-grade Gliomas, Kidney Chromophobe, and Thyroid Cancer, PAQR3 expression was positively correlated with OS and DSS, while in Rectum Adenocarcinoma, PAQR3 expression was negatively correlated with OS. PAQR3 high expression group Lower-grade Glioma and Glioblastoma, Pediatric Low-grade Gliomas, Uveal Melanoma, Kidney Chromophobe and DFI were positively correlated. PAQR3 can be used as a risk factor for the prognosis of multiple tumors. Then, we discussed the correlation between PAQR3 and immunology, and found that PAQR3 has a wide range of mutations in various tumor types, the most common mutation type is missense mutation, and common mutation types also include amplification, depth deletion, splicing, truncation and structural variation. Among the tumor samples with PAQR3 alterations, mutation occurred in all tumor samples except prostate adenocarcinoma and adrenal cortical carcinoma, head and neck squamous cell carcinoma, brain low-grade glioma, and kidney clear cell carcinoma, while esophageal adenocarcinoma had the highest total alteration frequency. PAQR3 was strongly associated with CNV in 18 tumors, particularly in Ovarian cancer, Lung squamous cell carcinoma, and Adenoid cystic carcinoma. On the other hand, PAQR3 has a higher SNV frequency in Uterine Corpus Endometrial Carcinoma, Skin Cutaneous Melanoma and Lung Adenocarcinoma, among which Uterine Corpus Endometrial Carcinoma has the highest SNV frequency. These results showed that PAQR3 expression levels were significantly correlated with tumor mutation load, microsatellite instability, neoantigens, and purity. In summary, PAQR3 can affect the tumor microenvironment and has potential for chemotherapy. Finally, we investigated the role of PAQR3 in tumor resistance and found that the expression of PAQR3 affects the efficacy of multiple chemotherapy drugs. Based on these studies, we found that PAQR3 plays an important role in cancer and has potential in tumor diagnosis and prognosis.

Construction of a necroptosis-related lncRNA signature for predicting prognosis and revealing the immune microenvironment in bladder cancer

BACKGROUND

Bladder cancer (BCa) is a common malignancy in the urinary system. Necroptosis, a recently discovered form of programmed cell death, is closely associated with the development and progression of various types of tumors. Targeting necroptosis through anti-cancer strategies has shown potential as a therapy for cancer. We aimed to develop a necroptosis-related lncRNAs (NRlncRNAs) risk model that can predict the survival and tumor immunity of BCa patients.

METHODS

We analyzed sequencing data obtained from the TCGA database, and applied least absolute shrinkage and selection operator (LASSO) and Cox regression analysis to identify crucial NRlncRNAs for building a risk model. Using the risk score, we categorized patients into high- and low-risk groups, and assessed the accuracy with the area under the receiver operating characteristic (AUROC) and Kaplan-Meier curves. We performed the RT-qPCR to detect the expression differences of the genes based on the risk model.

RESULTS

We identified a total of 296 NRlncRNAs, and 6 of them were included in the prognostic model. The AUC values for 1-, 3-, and 5-year predictions were 0.675, 0.726 and 0.734, respectively. Our risk model demonstrated excellent predictive performance and served as an independent predictor with high predictive power. Additionally, we performed PCA, TMB, GSEA analyses, and evaluated immune cell infiltration, to reveal significant differences between the high- and low-risk groups in functional signaling pathways, immunological status, and mutation profiles. Finally, we assessed the chemotherapeutic response of several drugs. According to the RT-qPCR results, we found that four NRlncRNAs of the risk model were more highly expressed in BCa cell lines than human immortalized uroepithelial cell line and regulated the occurrence and progression of bladder cancer.

CONCLUSION

We constructed a novel NRlncRNAs-associated risk model, which could predict the prognosis and immune response of BCa patients.

Harmonization of tumor mutation burden testing with comprehensive genomic profiling assays: an IQN Path initiative

BACKGROUND

Although conflicting results emerged from different studies, the tumor mutational burden (TMB) appears as one of most reliable biomarkers of sensitivity to immune checkpoint inhibitors. Several laboratories are reporting TMB values when performing comprehensive genomic profiling (CGP) without providing a clinical interpretation, due to the lack of validated cut-off values. The International Quality Network for Pathology launched an initiative to harmonize TMB testing with CGP assay and favor the clinical implementation of this biomarker.

METHODS

TMB evaluation was performed with three commercially available CGP panels, TruSight Oncology 500 (TSO500), Oncomine Comprehensive Plus Assay (OCA) and QIAseq Multimodal Panel (QIA), versus the reference assay FoundationOne CDx (F1CDx). Archived clinical samples derived from 60 patients with non-small cell lung cancer were used for TMB assessment. Adjusted cut-off values for each panel were calculated.

RESULTS

Testing was successful for 91.7%, 100%, 96.7% and 100% of cases using F1CDx, TSO500, OCA and QIA, respectively. The matrix comparison analysis, between the F1CDx and CGP assays, showed a linear correlation for all three panels, with a higher correlation between F1CDx and TSO500 (rho=0.88) than in the other two comparisons (rho=0.77 for QIA; 0.72 for OCA). The TSO500 showed the best area under the curve (AUC, value 0.96), with a statistically significant difference when compared with the AUC of OCA (0.83, p value=0.01) and QIA (0.88, p value=0.028). The Youden Index calculation allowed us to extrapolate TMB cut-offs of the different panels corresponding to the 10 mutations/megabase (muts/Mb) cut-off of F1CDx: 10.19, 10.4 and 12.37 muts/Mb for TSO500, OCA and QIA, respectively. Using these values, we calculated the relative accuracy measures for the three panels. TSO500 showed 86% specificity and 96% sensitivity, while OCA and QIA had lower yet similar values of specificity and sensitivity (73% and 88%, respectively).

CONCLUSION

This study estimated TMB cut-off values for commercially available CGP panels. The results showed a good performance of all panels on clinical samples and the calculated cut-offs support better accuracy measures for TSO500. The validated cut-off values can drive clinical interpretation of TMB testing in clinical research and clinical practice.

Molecular Characterization of TFE3-Rearranged Renal Cell Carcinoma: A Comparative Study With Papillary and Clear Cell Renal Cell Carcinomas

TFE3-rearranged renal cell carcinoma (rRCC) is a rare subtype of renal cell carcinomas belonging to the MiT family translocation RCC. To further elucidate the co-alterations that occur along with TFE3 fusions in rRCC, we characterized the genomic, transcriptional, and immune landscapes in comparison to clear cell (ccRCC) and papillary renal cell carcinoma (pRCC). Next-generation sequencing of RNA (whole transcriptome) and DNA (592-gene panel or whole exome) for rRCC (N = 20), pRCC (N = 20), and ccRCC samples (N = 392) was performed. Patients with rRCC were significantly younger and more frequently female (median 44.5 years, 75.0% female) as compared with patients with pRCC (68.5 years, 25.0% female; P < .05) and ccRCC (62.0 years, 27.8% female; P < .05). A total of 8 unique fusion partners were observed, including a novel fusion with SRRM2::TFE3 in 2 patients. ccRCC exhibited significantly higher mutation rates of VHL (0% rRCC, 0% pRCC, 78.7% ccRCC; P < .05) and PBMR1 (0% rRCC, 5.0% pRCC, 49.4% ccRCC; P < .05). The genomic landscapes of rRCC were sparse with no mutations occurring with a prevalence higher than 10% other than pTERT (18.2% rRCC, 0% pRCC, 9.2% ccRCC). rRCC were associated with significantly less M1 macrophages (0.8%) as compared with pRCC (1.4%) and ccRCC (2.7%) (P < .05), suggesting a cold tumor-immune microenvironment. However, rRCC were more commonly PD-L1+ (rRCC 50%, pRCC 19.0%, ccRCC 12.2%; P < .05). Gene set enrichment analysis showed that rRCC are enriched in genes related to oxidative phosphorylation when compared with both ccRCC and pRCC. Despite having a colder tumor-immune microenvironment than pRCC and ccRCC, increased PDL1+ rates in rRCC suggest a potential benefit from immune checkpoint inhibitor therapy.

Exploring Co-occurring POLE Exonuclease and Non-exonuclease Domain Mutations and Their Impact on Tumor Mutagenicity

POLE driver mutations in the exonuclease domain (ExoD driver) are prevalent in several cancers, including colorectal cancer and endometrial cancer, leading to dramatically ultra-high tumor mutation burden (TMB). To understand whether POLE mutations that are not classified as drivers (POLE Variant) contribute to mutagenesis, we assessed TMB in 447 POLE-mutated colorectal cancers, endometrial cancers, and ovarian cancers classified as TMB-high ≥10 mutations/Mb (mut/Mb) or TMB-low <10 mut/Mb. TMB was significantly highest in tumors with "POLE ExoD driver plus POLE Variant" (colorectal cancer and endometrial cancer, P < 0.001; ovarian cancer, P < 0.05). TMB increased with additional POLE variants (P < 0.001), but plateaued at 2, suggesting an association between the presence of these variants and TMB. Integrated analysis of AlphaFold2 POLE models and quantitative stability estimates predicted the impact of multiple POLE variants on POLE functionality. The prevalence of immunogenic neoepitopes was notably higher in the "POLE ExoD driver plus POLE Variant" tumors. Overall, this study reveals a novel correlation between POLE variants in POLE ExoD-driven tumors, and ultra-high TMB. Currently, only select pathogenic ExoD mutations with a reliable association with ultra-high TMB inform clinical practice. Thus, these findings are hypothesis-generating, require functional validation, and could potentially inform tumor classification, treatment responses, and clinical outcomes.

SIGNIFICANCE

Somatic POLE ExoD driver mutations cause proofreading deficiency that induces high TMB. This study suggests a novel modifier role for POLE variants in POLE ExoD-driven tumors, associated with ultra-high TMB. These data, in addition to future functional studies, may inform tumor classification, therapeutic response, and patient outcomes.

Enhancing the quality of panel-based tumor mutation burden assessment: a comprehensive study of real-world and in-silico outcomes

Targeted panel-based tumor mutation burden (TMB) assays are widely employed to guide immunotherapy for patients with solid tumors. However, the accuracy and consistency of this method can be compromised due to the variability in technical details across different laboratories, particularly in terms of panel size, somatic mutation detection and TMB calculation rules. Currently, systematic evaluations of the impact of these technical factors on existing assays and best practice recommendations remain lacking. We assessed the performance of 50 participating panel-based TMB assays involving 38 unique methods using cell line samples. In silico experiments utilizing TCGA MC3 datasets were performed to further dissect the impact of technical factors. Here we show that the panel sizes beyond 1.04 Mb and 389 genes are necessary for the basic discrete accuracy, as determined by over 40,000 synthetic panels. The somatic mutation detection should maintain a reciprocal gap of recall and precision less than 0.179 for reliable psTMB calculation results. The inclusion of synonymous, nonsense and hotspot mutations could enhance the accuracy of panel-based TMB assay. A 5% variant allele frequency cut-off is suitable for TMB assays using tumor samples with at least 20% tumor purity. In conclusion, this multicenter study elucidates the major technical factors as sources of variability in panel-based TMB assays and proposed comprehensive recommendations for the enhancement of accuracy and consistency. These findings will assist clinical laboratories in optimizing the methodological details through bioinformatic experiments to enhance the reliability of panel-based methods.

Ipilimumab and nivolumab combined with anthracycline-based chemotherapy in metastatic hormone receptor-positive breast cancer: a randomized phase 2b trial

BACKGROUND

Immune checkpoint inhibitors have shown minimal clinical activity in hormone receptor-positive metastatic breast cancer (HR+mBC). Doxorubicin and low-dose cyclophosphamide are reported to induce immune responses and counter regulatory T cells (Tregs). Here, we report the efficacy and safety of combined programmed cell death protein-1/cytotoxic T-lymphocyte-associated protein 4 blockade concomitant with or after immunomodulatory chemotherapy for HR+mBC.

METHODS

Patients with HR+mBC starting first-/second- line chemotherapy (chemo) were randomized 2:3 to chemotherapy (pegylated liposomal doxorubicin 20 mg/m2 every second week plus cyclophosphamide 50 mg by mouth/day in every other 2-week cycle) with or without concomitant ipilimumab (ipi; 1 mg/kg every sixth week) and nivolumab (nivo; 240 mg every second week). Patients in the chemo-only arm were offered cross-over to ipi/nivo without chemotherapy. Co-primary endpoints were safety in all patients starting therapy and progression-free survival (PFS) in the per-protocol (PP) population, defined as all patients evaluated for response and receiving at least two treatment cycles. Secondary endpoints included objective response rate, clinical benefit rate, Treg changes during therapy and assessment of programmed death-ligand 1 (PD-L1), mutational burden and immune gene signatures as biomarkers.

RESULTS

Eighty-two patients were randomized and received immune-chemo (N=49) or chemo-only (N=33), 16 patients continued to the ipi/nivo-only cross-over arm. Median follow-up was 41.4 months. Serious adverse events occurred in 63% in the immune-chemo arm, 39% in the chemo-only arm and 31% in the cross-over-arm. In the PP population (N=78) median PFS in the immune-chemo arm was 5.1 months, compared with 3.6 months in the chemo-only arm, with HR 0.94 (95% CI 0.59 to 1.51). Clinical benefit rates were 55% (26/47) and 48% (15/31) in the immune-chemo and chemo-only arms, respectively. In the cross-over-arm (ipi/nivo-only), objective responses were observed in 19% of patients (3/16) and clinical benefit in 25% (4/16). Treg levels in blood decreased after study chemotherapy. High-grade immune-related adverse events were associated with prolonged PFS. PD-L1 status and mutational burden were not associated with ipi/nivo benefit, whereas a numerical PFS advantage was observed for patients with a high Treg gene signature in tumor.

CONCLUSION

The addition of ipi/nivo to chemotherapy increased toxicity without improving efficacy. Ipi/nivo administered sequentially to chemotherapy was tolerable and induced clinical responses.

TRIAL REGISTRATION NUMBER

ClinicalTrials.gov Identifier: NCT03409198.

STX4 as a potential biomarker for predicting prognosis and guiding clinical treatment decisions in clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) represents a frequent subtype of kidney cancer, with the prognosis remaining poor for individuals with metastatic disease. Given its resistance to both radiation and chemotherapy, targeted therapies and immunotherapies have emerged as critical for effective ccRCC treatment. Within this context, the SNARE protein STX4, which is associated with malignant cancer cell migration, provides a promising focus. The underlying mechanism, however, requires further illumination. Furthermore, the influence of STX4 on the ccRCC tumor microenvironment remains to be determined. In our research, we utilized multiple databases and immunohistochemical staining to confirm differential STX4 expression and its prognostic implications. We evaluated the potential tumor-promoting function of STX4 in ccRCC cell lines through molecular studies. Additionally, we conducted functional enrichment analysis to delve deeper into the underlying mechanisms and performed immune infiltration and drug sensitivity analyses to assess the potential of STX4 as a prognostic biomarker and therapeutic target. Our study reveals that STX4 contributes to cancer progression by enhancing AKT expression and stimulating the activation of VEGF signaling pathways. Additionally, STX4 further fosters CD8+ T-cell infiltration and diminishes the percentage of CAFs and M2-TAMs. Our findings suggest that patients presenting higher STX4 levels may exhibit enhanced responsiveness to immunotherapy and higher sensitivity to the medications axitinib and everolimus. Finally, we propose STX4 expression assessment as a novel approach to predict patient response to respective immunotherapies and targeted treatments, hence potentially improving patient outcomes.

XRCC1: a potential prognostic and immunological biomarker in LGG based on systematic pan-cancer analysis

X-ray repair cross-complementation group 1 (XRCC1) is a pivotal contributor to base excision repair, and its dysregulation has been implicated in the oncogenicity of various human malignancies. However, a comprehensive pan-cancer analysis investigating the prognostic value, immunological functions, and epigenetic associations of XRCC1 remains lacking. To address this knowledge gap, we conducted a systematic investigation employing bioinformatics techniques across 33 cancer types. Our analysis encompassed XRCC1 expression levels, prognostic and diagnostic implications, epigenetic profiles, immune and molecular subtypes, Tumor Mutation Burden (TMB), Microsatellite Instability (MSI), immune checkpoints, and immune infiltration, leveraging data from TCGA, GTEx, CELL, Human Protein Atlas, Ualcan, and cBioPortal databases. Notably, XRCC1 displayed both positive and negative correlations with prognosis across different tumors. Epigenetic analysis revealed associations between XRCC1 expression and DNA methylation patterns in 10 cancer types, as well as enhanced phosphorylation. Furthermore, XRCC1 expression demonstrated associations with TMB and MSI in the majority of tumors. Interestingly, XRCC1 gene expression exhibited a negative correlation with immune cell infiltration levels, except for a positive correlation with M1 and M2 macrophages and monocytes in most cancers. Additionally, we observed significant correlations between XRCC1 and immune checkpoint gene expression levels. Lastly, our findings implicated XRCC1 in DNA replication and repair processes, shedding light on the precise mechanisms underlying its oncogenic effects. Overall, our study highlights the potential of XRCC1 as a prognostic and immunological pan-cancer biomarker, thereby offering a novel target for tumor immunotherapy.