The FDA approval of pembrolizumab for adult and pediatric patients with tumor mutational burden (TMB) ≥10: a decision centered on empowering patients and their physicians

Clinical performance of the TrueMark™ MSI assay for microsatellite instability detection in a Chinese colorectal cancer cohort

BACKGROUND

Microsatellite instability (MSI) and mismatch repair (MMR) detection is valuable in assessing prognosis and treatment options. However, the conventional detection methods such as immunohistochemistry (IHC) are limited by not fully consistent results as well as a long turnaround time. TrueMark™ MSI Assay is a novel solution for MSI analysis, but lack of research support in the Chinese colorectal cancer (CRC) patients.

MATERIALS AND METHODS

60 dMMR and 60 pMMR CRC samples identified by IHC were collected and their MSI status were detected using TrueMark™ MSI assay with an expanded panel of 13 markers. The overall performance and diagnostic concordance between TrueMark™ MSI test and MMR IHC analysis were assessed and analyzed.

RESULTS

According to the TrueMark™ test, 55 out of the 120 (45.8 %) CRCs were identified as MSI-high (MSI-H) with an instability at ≥ 4/13 markers. Compared with the MMR IHC analysis, an overall percent agreement of 94.2 % and a Kappa of 0.883 were achieved. For the seven inconsistent samples, tumor mutation burden analysis was performed and the results supported the diagnosis by TrueMark™ test. To confirm the robustness of the above findings, a validation was performed in an independent cohort comprising 51 consecutive CRCs. Furthermore, an optimized panel composed of NR-21, NR-24, NR-27, ABI-16, ABI-17 and ABI-20B was developed by multivariate logistic regression model, and showed 100 % agreement with the 13-marker panel for MSI detection in both the derivation and validation sets.

CONCLUSION

TrueMark™ MSI provides a fast, reliable and highly automated solution to MSI detection in Chinese CRC patients, and the new 6-marker panel we established shows promise deserving further evaluation.

Multi-omics analysis unveils the predictive value of IGF2BP3/SPHK1 signaling in cancer stem cells for prognosis and immunotherapeutic response in muscle-invasive bladder cancer

BACKGROUND

Muscle invasive bladder cancer (MIBC) is a life-threatening malignant tumor characterized by high metastasis rates, poor prognosis, and limited treatment options. Immune checkpoint inhibitors (ICIs) targeting PD-1 and PD-L1 represent an emerging treatment for MIBC immunotherapy. However, the characteristics of patients likely to benefit from immunotherapy remain unclear.

METHODS

We performed single-cell mass cytometry (CyTOF) analysis of 179,483 single cells to characterize potential immunotherapy-related cancer stem cells (CSCs)-like populations in the tumor microenvironment of 38 MIBC tissues. The upregulated expression of IGF2BP3 in CD274 + ALDH + CSC-like cells, which was associated with poor clinical prognosis, was analyzed by bulk RNA-sequencing data from an in-house cohort. The functional role of IGF2BP3 was determined through cell proliferation, colony formation, cell apoptosis and sphere formation assays. The regulation of SPHK1 expression by IGF2BP3 was  investigated using methylated RNA immunoprecipitation sequencing (MeRIP-seq) and bulk RNA-sequencing (bulk RNA-seq). We further utilized single-nucleus RNA sequencing (snRNA-seq) data from 67,988 cells of 25 MIBC tissues and single-cell RNA sequencing (scRNA-seq) data from MIBC patient-derived organoids to characterize the molecular features of bladder cancer cells co-expressing IGF2BP3 and SPHK1. Spatial transcriptomics (ST) and co-detection by indexing (CODEX) analysis were used to describe the spatial distribution and interactions of IGF2BP3 + SPHK1 + bladder cancer cells and immune cells.

RESULTS

A subset of CD274 + ALDH + CSC-like cells was identified, associating with immunosuppression and low survival rates in MIBC patients. IGF2BP3, an m6A reader gene, was found to be upregulated in the CD274 + ALDH + CSC-like cell population and linked to poor clinical prognosis in MIBC. Knockout of IGF2BP3 dramatically promoted cell apoptosis and reduced cell proliferation in T24 cells. By integrating MeRIP-seq and bulk RNA-seq analyses, we identified SPHK1 served as a substrate for IGF2BP3 in an m6A-dependent manner. Further snRNA-seq, scRNA-seq, ST, and CODEX analysis revealed a closer topographical distance between IGF2BP3 + SPHK1 + bladder cancer cells and exhausted CD8 + T cells, providing one explanation for the superior response to immunotherapy in IGF2BP3 + SPHK1 + bladder cancer cells-enriched patients. Finally, an ICI-associated signature was developed based on the enriched genes of IGF2BP3 + SPHK1 + bladder cancer cells, and its potential ability to predict the response to immunotherapy was validated in two independent immunotherapy cohort.

CONCLUSIONS

Our study highlighted the critical involvement of the IGF2BP3/SPHK1 signaling in maintaining the stemness of CSCs and promoting MIBC progression. Additionally, these findings suggested that the IGF2BP3/SPHK1 signaling might serve as a biomarker for prognosis and immunotherapy response in MIBC.

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 evolving landscape of tissue-agnostic therapies in precision oncology

Tumor-agnostic therapies represent a paradigm shift in oncology by altering the traditional means of characterizing tumors based on their origin or location. Instead, they zero in on specific genetic anomalies responsible for fueling malignant growth. The watershed moment for tumor-agnostic therapies arrived in 2017, with the US Food and Drug Administration's historic approval of pembrolizumab, an immune checkpoint inhibitor. This milestone marked the marriage of genomics and immunology fields, as an immunotherapeutic agent gained approval based on genomic biomarkers, specifically, microsatellite instability-high or mismatch repair deficiency (dMMR). Subsequently, the approval of NTRK inhibitors, designed to combat NTRK gene fusions prevalent in various tumor types, including pediatric cancers and adult solid tumors, further underscored the potential of tumor-agnostic therapies. The US Food and Drug Administration approvals of targeted therapies (BRAF V600E, RET fusion), immunotherapies (tumor mutational burden ≥10 mutations per megabase, dMMR) and an antibody-drug conjugate (Her2-positive-immunohistochemistry 3+ expression) with pan-cancer efficacy have continued, offering newfound hope to patients grappling with advanced solid tumors that harbor particular biomarkers. In this comprehensive review, the authors delve into the expansive landscape of tissue-agnostic targets and drugs, shedding light on the rationale underpinning this approach, the hurdles it faces, presently approved therapies, voices from the patient advocacy perspective, and the tantalizing prospects on the horizon. This is a welcome advance in oncology that transcends the boundaries of histology and location to provide personalized options.

OX40/OX40 ligand and its role in precision immune oncology

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

Precision oncology: current and future platforms for treatment selection

Genomic profiling of hundreds of cancer-associated genes is now a component of routine cancer care. DNA sequencing can identify mutations, mutational signatures, and structural alterations predictive of therapy response and assess for heritable cancer risk, but it has been less useful for identifying predictive biomarkers of sensitivity to cytotoxic chemotherapies, antibody drug conjugates, and immunotherapies. The clinical adoption of molecular profiling platforms such as RNA sequencing better suited to identifying those patients most likely to respond to immunotherapies and drug combinations will be critical to expanding the benefits of precision oncology. This review discusses the potential advantages of innovative molecular and functional profiling platforms designed to replace or complement targeted DNA sequencing and the major hurdles to their clinical adoption.

Plasma extracellular vesicle long RNA profiling identifies a predictive signature for immunochemotherapy efficacy in lung squamous cell carcinoma

Introduction

The introduction of Immune Checkpoint Inhibitors (ICIs) has marked a paradigm shift in treating Lung Squamous Cell Carcinoma (LUSC), emphasizing the urgent need for precise molecular biomarkers to reliably forecast therapeutic efficacy. This study aims to identify potential biomarkers for immunochemotherapy efficacy by focusing on plasma extracellular vesicle (EV)-derived long RNAs (exLRs).

Methods

We enrolled 78 advanced LUSC patients undergoing first-line immunochemotherapy. Plasma samples were collected, and exLR sequencing was conducted to establish baseline profiles. A retrospective analysis was performed on 42 patients to identify differentially expressed exLRs. Further validation of the top differentially expressed exLRs was conducted using quantitative reverse transcription PCR (qRT-PCR). Univariate Cox analysis was applied to determine the prognostic significance of these exLRs. Based on these findings, we developed a predictive signature (p-Signature).

Results

In the retrospective analysis of 42 patients, we identified 460 differentially expressed exLRs, with pathways related to leukocyte migration notably enriched among non-responders. Univariate Cox analysis revealed 45 exLRs with prognostic significance. The top 6 protein-coding exLRs were validated using qRT-PCR, identifying CXCL8, SSH3, and SDHAF1 as differentially expressed between responders and non-responders. The p-Signature, comprising these three exLRs, demonstrated high accuracy in distinguishing responders from non-responders, with an Area Under the Curve (AUC) of 0.904 in the retrospective cohort and 0.812 in the prospective cohort.

Discussion

This study highlighted the potential of plasma exLR profiles in predicting LUSC treatment efficacy. Intriguingly, lower p-Signature scores were associated with increased abundance of activated CD4+ and CD8+ T cells, indicating a more robust immune environment. These findings suggest that the p-Signature could serve as a valuable tool in guiding personalized and effective therapeutic strategies for LUSC.

High-grade neuroendocrine head and neck cancer: Case series and review of the literature

BACKGROUND

High-grade neuroendocrine cancers (NEC) of the head and neck (HN) are rare and aggressive, accounting for ≤1 % of all HN cancers, with a 5-year overall survival (OS) of ≤20 %. This case series examines clinical characteristics, treatments, and outcomes of patients diagnosed at a regional UK HN cancer centre over the last 23 years.

METHODS

A retrospective review of medical records was conducted for all patients diagnosed with NEC HN from 1st January 2000 until 1st March 2023 at Velindre Cancer Centre.

RESULTS

During the study period, 19 cases of NEC HN were identified, primarily affecting males (n = 15, 79 %). Median age of 67 years (range: 44-86). At diagnosis, 32 % of patients (n = 6) were smokers. The most common primary tumour sites were larynx (n = 5, 26.3 %) and sinonasal (n = 5, 26.3 %). Most patients presented with advanced loco-regional disease or distant metastasis, with stage IVA (n = 6, 32 %) and stage IVC (n = 6, 32 %) being the most common. The key pathology marker was synaptophysin, present in 100 % of the tested patients (n = 15). In the study, of the 12 patients with non-metastatic disease, 10 received a combination of treatments that included radiotherapy (RT). Some of these patients also received chemotherapy (CT) at the same time as their radiotherapy. Surgery alone was used in two patients with stage II disease. Seven subjects had complete responses, and one achieved a partial response. Among the seven metastatic patients, three received CT, and one underwent palliative RT, all achieving a partial response. In all cases, the CT used was carboplatin and etoposide. After a median follow-up of 11 months (range: 1-96), the median OS was 27 months for the overall population, 51 months for those treated radically, and three months for metastatic patients with palliative treatment. The 1-year OS for all patients was 54.3 %, the 2-year OS was 46.5 %, and the 5-year OS was 23.3 %. Among patients treated radically, these rates were 65.3 %, 52.2 %, and 26.1 %, respectively. For patients treated palliatively, the 1-year OS was 33.3 %.

CONCLUSION

This case series contributes preliminary observations on the characteristics and management of non-metastatic NEC HN, suggesting potential benefits from multimodality treatment strategies. Given the small cohort size, these observations should be interpreted cautiously and seen as a foundation for further research.

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.

Immune Microenvironment in Childhood Cancers: Characteristics and Therapeutic Challenges

The tumor immune microenvironment is pivotal in cancer initiation, advancement, and regulation. Its molecular and cellular composition is critical throughout the disease, as it can influence the balance between suppressive and cytotoxic immune responses within the tumor's vicinity. Studies on the tumor immune microenvironment have enriched our understanding of the intricate interplay between tumors and their immunological surroundings in various human cancers. These studies illuminate the role of significant components of the immune microenvironment, which have not been extensively explored in pediatric tumors before and may influence the responsiveness or resistance to therapeutic agents. Our deepening understanding of the pediatric tumor immune microenvironment is helping to overcome challenges related to the effectiveness of existing therapeutic strategies, including immunotherapies. Although in the early stages, targeted therapies that modulate the tumor immune microenvironment of pediatric solid tumors hold promise for improved outcomes. Focusing on various aspects of tumor immune biology in pediatric patients presents a therapeutic opportunity that could improve treatment outcomes. This review offers a comprehensive examination of recent literature concerning profiling the immune microenvironment in various pediatric tumors. It seeks to condense research findings on characterizing the immune microenvironment in pediatric tumors and its impact on tumor development, metastasis, and response to therapeutic modalities. It covers the immune microenvironment's role in tumor development, interactions with tumor cells, and its impact on the tumor's response to immunotherapy. The review also discusses challenges targeting the immune microenvironment for pediatric cancer therapies.

Pan-Cancer Molecular Biomarkers: A Paradigm Shift in Diagnostic Pathology

The rapid adoption of next-generation sequencing in clinical oncology has enabled the detection of molecular biomarkers shared between multiple tumor types. These pan-cancer biomarkers include sequence-altering mutations, copy number changes, gene rearrangements, and mutational signatures and have been demonstrated to predict response to targeted therapy. This article reviews issues surrounding current and emerging pan-cancer molecular biomarkers in clinical oncology: technological advances that enable the broad detection of cancer mutations across hundreds of genes, the spectrum of driver and passenger mutations derived from human cancer genomes, and implications for patient care now and in the near future.

SWI/SNF family mutations in advanced NSCLC: genetic characteristics and immune checkpoint inhibitors' therapeutic implication

BACKGROUND

SWItch/Sucrose NonFermentable (SWI/SNF) mutations have garnered increasing attention because of their association with unfavorable prognosis. However, the genetic landscape of SWI/SNF family mutations in Chinese non-small-cell lung cancer (NSCLC) is poorly understood. In addition, the optimal treatment strategy has not yet been determined.

PATIENTS AND METHODS

We collected sequencing data on 2027 lung tumor samples from multiple centers in China to comprehensively analyze the genomic characteristics of the SWI/SNF family within the Chinese NSCLC population. Meanwhile, 519 patients with NSCLC from Sun Yat-sen University Cancer Center were enrolled to investigate the potential implications of immunotherapy on patients with SWI/SNF mutations and to identify beneficial subpopulations. We also validated our findings in multiple publicly available cohorts.

RESULTS

Approximately 15% of Chinese patients with lung cancer harbored mutations in the SWI/SNF chromatin remodeling complex, which were mutually exclusive to the EGFR mutations. Patients with SWI/SNFmut NSCLC who received first-line chemoimmunotherapy had better survival outcomes than those who received chemotherapy alone (median progression-free survival: 8.70 versus 6.93 months; P = 0.028). This finding was also confirmed by external validation using the POPLAR/OAK cohort. SWI/SNFmut NSCLC is frequently characterized by high tumor mutational burden and concurrent TP53 or STK11/KEAP mutations. Further analysis indicated that TP53 and STK11/KEAP1 mutations could be stratifying factors in facilitating personalized immunotherapy and guiding patient selection.

CONCLUSIONS

This study provides a step forward in understanding the genetic and immunological characterization of SWI/SNF genetic alterations. Moreover, our study reveals substantial benefits of immunotherapy over chemotherapy for SWI/SNF-mutant patients, especially the SWI/SNFmut and TP53mut subgroups.

Multi-omic analysis identifies hypoalbuminemia as independent biomarker of poor outcome upon PD-1 blockade in metastatic melanoma

We evaluated the prognostic value of hypoalbuminemia in context of various biomarkers at baseline, including clinical, genomic, transcriptomic, and blood-based markers, in patients with metastatic melanoma treated with anti-PD-1 monotherapy or anti-PD-1/anti-CTLA-4 combination therapy (n = 178). An independent validation cohort (n = 79) was used to validate the performance of hypoalbuminemia compared to serum LDH (lactate dehydrogenase) levels. Pre-treatment hypoalbuminemia emerged as the strongest predictor of poor outcome for both OS (HR = 4.01, 95% CI 2.10-7.67, Cox P = 2.63e-05) and PFS (HR = 3.72, 95% CI 2.06-6.73, Cox P = 1.38e-05) in univariate analysis. In multivariate analysis, the association of hypoalbuminemia with PFS was independent of serum LDH, IFN-γ signature expression, TMB, age, ECOG PS, treatment line, treatment type (combination or monotherapy), brain and liver metastasis (HR = 2.76, 95% CI 1.24-6.13, Cox P = 0.0131). Our validation cohort confirmed the prognostic power of hypoalbuminemia for OS (HR = 1.98, 95% CI 1.16-3.38; Cox P = 0.0127) and was complementary to serum LDH in analyses for both OS (LDH-adjusted HR = 2.12, 95% CI 1.2-3.72, Cox P = 0.00925) and PFS (LDH-adjusted HR = 1.91, 95% CI 1.08-3.38, Cox P = 0.0261). In conclusion, pretreatment hypoalbuminemia was a powerful predictor of outcome in ICI in melanoma and showed remarkable complementarity to previously established biomarkers, including high LDH.

Genetic analysis of cervical cancer with lymph node metastasis

OBJECTIVE

To find out the differences in gene characteristics between cervical cancer patients with and without lymph node metastasis, and to provide reference for therapy.

METHODS

From January 2018 to June 2022, recurrent cervical cancer patients 39 cases with lymph node metastasis and 73 cases without lymph node metastasis underwent testing of 1,021 cancer-related genes by next-generation sequencing. Maftools software was used to analyze somatic single nucleotide/insertion-deletion variation mutation, co-occurring mutation, cosmic mutation characteristics, oncogenic signaling pathways.

RESULTS

EP300 and FBXW7 were significantly enriched in lymph node-positive patients. Lymph node-positive patients with EP300 or FBXW7 mutations had lower overall survival (OS) after recurrence. Both lymph node-positive and -negative patients had plenty of co-occurring mutations but few mutually exclusive mutations. Lymph node-positive co-occurring mutation number ≥6 had lower OS, while lymph node-negative co-occurring mutation number ≥3 had lower OS after recurrence. The etiology of SBS3 was defects in DNA double strand break repair by homologous recombination, which exclusively exist in lymph node-positive patients. There was no difference in median tumor mutation burden (TMB) between positive and negative lymph nodes, but TMB was significantly associated with PIK3CA mutation.

CONCLUSION

The somatic SNV/Indels of EP300 and FBXW7, SBS3 homologous recombination-mediated DNA repair defect were enriched in lymph node-positive patients. For lymph node-positive patients, EP300 or FBXW7 mutations predicted poor prognosis. No matter lymph node-positive or negative, more co-occurring mutation number predicted poor prognosis. PIK3CA mutation may account for the higher TMB and help identify patients who benefit from immunotherapy.

Precision Oncology in Pediatric Cancer Surgery

Pediatric precision oncology has provided a greater understanding of the wide range of molecular alterations in difficult-to-treat or rare tumors with the aims of increasing survival as well as decreasing toxicity and morbidity from current cytotoxic therapies. In this article, the authors discuss the current state of pediatric precision oncology which has increased access to novel targeted therapies while also providing a framework for clinical implementation in this unique population. The authors evaluate the targetable mutations currently under investigation-with a focus on pediatric solid tumors-and discuss the key surgical implications associated with novel targeted therapies.

Harnessing the Potential of Real-World Evidence in the Treatment of Colorectal Cancer: Where Do We Stand?

OPINION STATEMENT

Treatment guidelines for colorectal cancer (CRC) are primarily based on the results of randomized clinical trials (RCTs), the gold standard methodology to evaluate safety and efficacy of oncological treatments. However, generalizability of trial results is often limited due to stringent eligibility criteria, underrepresentation of specific populations, and more heterogeneity in clinical practice. This may result in an efficacy-effectiveness gap and uncertainty regarding meaningful benefit versus treatment harm. Meanwhile, conduct of traditional RCTs has become increasingly challenging due to identification of a growing number of (small) molecular subtypes. These challenges-combined with the digitalization of health records-have led to growing interest in use of real-world data (RWD) to complement evidence from RCTs. RWD is used to evaluate epidemiological trends, quality of care, treatment effectiveness, long-term (rare) safety, and quality of life (QoL) measures. In addition, RWD is increasingly considered in decision-making by clinicians, regulators, and payers. In this narrative review, we elaborate on these applications in CRC, and provide illustrative examples. As long as the quality of RWD is safeguarded, ongoing developments, such as common data models, federated learning, and predictive modelling, will further unfold its potential. First, whenever possible, we recommend conducting pragmatic trials, such as registry-based RCTs, to optimize generalizability and answer clinical questions that are not addressed in registrational trials. Second, we argue that marketing approval should be conditional for patients who would have been ineligible for the registrational trial, awaiting planned (non) randomized evaluation of outcomes in the real world. Third, high-quality effectiveness results should be incorporated in treatment guidelines to aid in patient counseling. We believe that a coordinated effort from all stakeholders is essential to improve the quality of RWD, create a learning healthcare system with optimal use of trials and real-world evidence (RWE), and ultimately ensure personalized care for every CRC patient.

Multi-omic analysis in carcinoma of unknown primary (CUP): therapeutic impact of knowing the unknown

Carcinoma of unknown primary (CUP) is a difficult-to-manage malignancy. Multi-omic profiles and treatment outcome vs. degree of precision matching were assessed. Tumours underwent next-generation sequencing (NGS) [tissue and/or blood-derived cell-free DNA (cfDNA)]. Selected patients had transcriptome-based immune profiling and/or programmed cell death 1 ligand 1 (PD-L1) immunohistochemistry analysis. Patients could be reviewed by a Molecular Tumor Board, but physicians chose the therapy. Of 6497 patients in the precision database, 97 had CUP. The median number of pathogenic tissue genomic alterations was 4 (range, 0-25), and for cfDNA, was 2 (range, 0-9). Each patient had a distinct molecular landscape. Food and Drug Administration (FDA)-approved biomarkers included the following: PD-L1+ ≥ 1%, 30.9% of CUPs tested; microsatellite instability, 3.6%; tumour mutational burden ≥ 10 mutations·Mb-1, 23%; and neurotrophic receptor tyrosine kinase (NTRK) fusions, 0%. RNA-based immunograms showed theoretically druggable targets: lymphocyte activation gene 3 protein (LAG-3), macrophage colony-stimulating factor 1 receptor (CSF1R), adenosine receptor A2 (ADORA2) and indoleamine 2,3-dioxygenase 1 (IDO1). Overall, 56% of patients had ≥ 1 actionable biomarker (OncoKB database). To quantify the degree of matching (tumours to drugs), a Matching Score (MS; roughly equivalent to number of alterations targeted/total number of deleterious alterations) was calculated post hoc. Comparing evaluable treated patients [MS high, > 50% (N = 15) vs. low ≤ 50% (N = 47)], median progression-free survival was 10.4 vs. 2.8 months (95% CI 0.11-0.64; HR 0.27; P = 0.002); survival, 15.8 vs. 6.9 months (95% CI 0.17-1.16; HR 0.45; P = 0.09); and clinical benefit rate (stable disease ≥ 6 months/partial/complete response), 71% vs. 24% (P = 0.003). Higher MS was the only factor that predicted improvement in outcome variables after multivariate analysis. In conclusion, CUPs are molecularly complex. Treatments with high degrees of matching to molecular alterations (generally achieved by individualized combinations) correlated with improved outcomes.

Histology agnosticism: Infra-molecularizing disease?

The term "molecularization" has been used by historians and sociologists of science to describe the transition from an anatomic view of the body to a submicroscopic one, where health and illness, indeed life itself, are increasingly defined in terms of an individual's "genetic landscape." Here we introduce the notion of the infra-molecular as a way of extending and nuancing the molecularization trope as it applies to the domain of (post)genomic oncology. In particular we look at how infra-molecularity is enacted in practice as part of the so-called "histology-agnostic" turn in clinical cancer research and care. Drawing on fieldwork in North American oncology settings, we analyze how histology agnosticism partially reconfigures knowledge and practice across the linked domains of drug development and clinical trials, therapeutic decision making, and regulation, and the implications of this for an ongoing revision of how we understand the biopathology and temporality of cancer. We show how, in practice, the inframolecular gaze entails a "return" of histology as a modulator of histology-agnostic drugs and background for interpretation of mutational complexity.

Tissue-Agnostic Cancer Therapy Approvals

Tumor-agnostic, or histology-agnostic, cancer therapy marks a groundbreaking evolution in the realm of precision oncology. In stark contrast to conventional cancer treatments that categorize malignancies based on their tissue of origin (eg, breast, lung, renal cell, etc), tumor-agnostic therapies transcend histologic boundaries, honing in on the genetic and molecular attributes of tumors, regardless of their location. This article offers a comprehensive review of the current landscape of tissue-agnostic cancer therapies and provides clinical insights to empower surgical oncologists with a deeper understanding of these innovative therapeutic approaches.

Identification of an immune-related gene signature for predicting prognosis and immunotherapy efficacy in liver cancer via cell-cell communication

BACKGROUND

Liver cancer is one of the deadliest malignant tumors worldwide. Immunotherapy has provided hope to patients with advanced liver cancer, but only a small fraction of patients benefit from this treatment due to individual differences. Identifying immune-related gene signatures in liver cancer patients not only aids physicians in cancer diagnosis but also offers personalized treatment strategies, thereby improving patient survival rates. Although several methods have been developed to predict the prognosis and immunotherapeutic efficacy in patients with liver cancer, the impact of cell-cell interactions in the tumor microenvironment has not been adequately considered.

AIM

To identify immune-related gene signals for predicting liver cancer prognosis and immunotherapy efficacy.

METHODS

Cell grouping and cell-cell communication analysis were performed on single-cell RNA-sequencing data to identify highly active cell groups in immune-related pathways. Highly active immune cells were identified by intersecting the highly active cell groups with B cells and T cells. The significantly differentially expressed genes between highly active immune cells and other cells were subsequently selected as features, and a least absolute shrinkage and selection operator (LASSO) regression model was constructed to screen for diagnostic-related features. Fourteen genes that were selected more than 5 times in 10 LASSO regression experiments were included in a multivariable Cox regression model. Finally, 3 genes (stathmin 1, cofilin 1, and C-C chemokine ligand 5) significantly associated with survival were identified and used to construct an immune-related gene signature.

RESULTS

The immune-related gene signature composed of stathmin 1, cofilin 1, and C-C chemokine ligand 5 was identified through cell-cell communication. The effectiveness of the identified gene signature was validated based on experimental results of predictive immunotherapy response, tumor mutation burden analysis, immune cell infiltration analysis, survival analysis, and expression analysis.

CONCLUSION

The findings suggest that the identified gene signature may contribute to a deeper understanding of the activity patterns of immune cells in the liver tumor microenvironment, providing insights for personalized treatment strategies.

Impact on costs and outcomes of multi-gene panel testing for advanced solid malignancies: a cost-consequence analysis using linked administrative data

Background

To date, economic analyses of tissue-based next generation sequencing genomic profiling (NGS) for advanced solid tumors have typically required models with assumptions, with little real-world evidence on overall survival (OS), clinical trial enrollment or end-of-life quality of care.

Methods

Cost consequence analysis of NGS testing (555 or 161-gene panels) for advanced solid tumors through the OCTANE clinical trial (NCT02906943). This is a longitudinal, propensity score-matched retrospective cohort study in Ontario, Canada using linked administrative data. Patients enrolled in OCTANE at Princess Margaret Cancer Centre from August 2016 until March 2019 were matched with contemporary patients without large gene panel testing from across Ontario not enrolled in OCTANE. Patients were matched according to 19 patient, disease and treatment variables. Full 2-year follow-up data was available. Sensitivity analyses considered alternative matched cohorts. Main Outcomes were mean per capita costs (2019 Canadian dollars) from a public payer's perspective, OS, clinical trial enrollment and end-of-life quality metrics.

Findings

There were 782 OCTANE patients with 782 matched controls. Variables were balanced after matching (standardized difference <0.10). There were higher mean health-care costs with OCTANE ($79,702 vs. $59,550), mainly due to outpatient and specialist visits. Publicly funded drug costs were less with OCTANE ($20,015 vs. $24,465). OCTANE enrollment was not associated with improved OS (restricted mean survival time [standard error]: 1.50 (±0.03) vs. 1.44 (±0.03) years, log-rank p = 0.153), varying by tumor type. In five tumor types with ≥35 OCTANE patients, OS was similar in three (breast, colon, uterus, all p > 0.40), and greater in two (ovary, biliary, both p < 0.05). OCTANE was associated with greater clinical trial enrollment (25.4% vs. 9.5%, p < 0.001) and better end-of-life quality due to less death in hospital (10.2% vs. 16.4%, p = 0.003). Results were robust in sensitivity analysis.

Interpretation

We found an increase in healthcare costs associated with multi-gene panel testing for advanced cancer treatment. The impact on OS was not significant, but varied across tumor types. OCTANE was associated with greater trial enrollment, lower publicly funded drug costs and fewer in-hospital deaths suggesting important considerations in determining the value of NGS panel testing for advanced cancers.

Funding

T.P H holds a research grant provided by the Ontario Institute for Cancer Research through funding provided by the Government of Ontario (#IA-035 and P.HSR.158) and through funding of the Canadian Network for Learning Healthcare Systems and Cost-Effective 'Omics Innovation (CLEO) via Genome Canada (G05CHS).

Integrative score based on CDK6, PD-L1 and TMB predicts response to platinum-based chemotherapy and PD-1/PD-L1 blockade in muscle-invasive bladder cancer

BACKGROUND

Cyclin-dependent kinase 6 (CDK6) was proved to be an important regulator in the progression of cell cycle and has been a promising therapeutic target in cancer treatment. However, the clinical significance of CDK6 in muscle-invasive bladder cancer (MIBC) remains obscure. Herein, we attempt to explore the clinical relevance of CDK6 and assess the feasibility of the integrative model to predict immune checkpoint blockade (ICB) response.

METHODS

This study enrolled 933 patients with muscle-invasive bladder cancer (MIBC) from Zhongshan Hospital (ZSHS), The Cancer Genome Atlas (TCGA), Chemo, IMvigor210 and UC-GENOME cohorts. Kaplan-Meier survival and Cox regression analyses were performed to assess clinical outcomes based on CDK6 expression.

RESULTS

High CDK6 expression conferred poor prognosis and superior response to platinum-based chemotherapy but inferior response to ICB in MIBC. Furthermore, the integrative model named response score based on CDK6, PD-L1 and TMB could better predict the response to ICB and chemotherapy. Patients with higher response scores were characterised by inflamed immune microenvironment and genomic instability.

CONCLUSIONS

CDK6 expression was correlated with prognosis and therapy response in MIBC. Integration of CDK6, PD-L1 and TMB could better identify patients who were most likely to benefit from ICB and chemotherapy.

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.

Tumor Copy Number Alteration Burden as a Predictor for Resistance to Immune Checkpoint Blockade across Different Cancer Types

Immune checkpoint blockade (ICB) benefits only a subset of advanced cancer patients, and predictive biomarkers for immunotherapy response are needed. Recently, copy number alteration (CNA) burden has been proposed to predict ICB resistance. We assessed this finding using the publicly accessible data for 1661 ICB-treated patients whose tumors were profiled by MSK-IMPACT, an approved targeted assay in clinical care. We tested the hypothesis that the continuous increase in CNA burden is associated with poor overall survival following ICB. In addition, we hypothesized that the combinatorial biomarkers of tumor mutational burden (TMB) and CNA burden would better stratify patients for immune status and ICB response. Of the 1661 cases, 79% (n = 1307) were treated with anti PD-1/PD-L1 and the remaining 21% (n = 354) with anti CTLA-4 or the combination of both. In a multivariate analysis, increase in CNA burden was associated with poor overall survival [HR = 1.52, 95% CI (1.01-2.30), p = 0.04]. The combination of biomarkers TMB and CNA burden stratified patients into four clinically distinct subsets among which "LowTMB/HighCNA" showed the worst survival (p < 0.0001). The four patient subsets had unique CNA profiles and enriched pathways, which could predict transcriptional and phenotypic effects related to immune signaling and CD8+ T-cell abundance in the tumor microenvironment. CNA burden was associated with poor overall survival in patients receiving ICB and could improve patient stratification when incorporated with TMB. These findings may guide patient selection for immunotherapy or alternative strategies.

Paradigm Shift: A Comprehensive Review of Ovarian Cancer Management in an Era of Advancements

Ovarian cancer (OC) is the female genital malignancy with the highest lethality. Patients present a poor prognosis mainly due to the late clinical presentation allied with the common acquisition of chemoresistance and a high rate of tumour recurrence. Effective screening, accurate diagnosis, and personalised multidisciplinary treatments are crucial for improving patients' survival and quality of life. This comprehensive narrative review aims to describe the current knowledge on the aetiology, prevention, diagnosis, and treatment of OC, highlighting the latest significant advancements and future directions. Traditionally, OC treatment involves the combination of cytoreductive surgery and platinum-based chemotherapy. Although more therapeutical approaches have been developed, the lack of established predictive biomarkers to guide disease management has led to only marginal improvements in progression-free survival (PFS) while patients face an increasing level of toxicity. Fortunately, because of a better overall understanding of ovarian tumourigenesis and advancements in the disease's (epi)genetic and molecular profiling, a paradigm shift has emerged with the identification of new disease biomarkers and the proposal of targeted therapeutic approaches to postpone disease recurrence and decrease side effects, while increasing patients' survival. Despite this progress, several challenges in disease management, including disease heterogeneity and drug resistance, still need to be overcome.

Artificial intelligence for predictive biomarker discovery in immuno-oncology: a systematic review

BACKGROUND

The widespread use of immune checkpoint inhibitors (ICIs) has revolutionised treatment of multiple cancer types. However, selecting patients who may benefit from ICI remains challenging. Artificial intelligence (AI) approaches allow exploitation of high-dimension oncological data in research and development of precision immuno-oncology.

MATERIALS AND METHODS

We conducted a systematic literature review of peer-reviewed original articles studying the ICI efficacy prediction in cancer patients across five data modalities: genomics (including genomics, transcriptomics, and epigenomics), radiomics, digital pathology (pathomics), and real-world and multimodality data.

RESULTS

A total of 90 studies were included in this systematic review, with 80% published in 2021-2022. Among them, 37 studies included genomic, 20 radiomic, 8 pathomic, 20 real-world, and 5 multimodal data. Standard machine learning (ML) methods were used in 72% of studies, deep learning (DL) methods in 22%, and both in 6%. The most frequently studied cancer type was non-small-cell lung cancer (36%), followed by melanoma (16%), while 25% included pan-cancer studies. No prospective study design incorporated AI-based methodologies from the outset; rather, all implemented AI as a post hoc analysis. Novel biomarkers for ICI in radiomics and pathomics were identified using AI approaches, and molecular biomarkers have expanded past genomics into transcriptomics and epigenomics. Finally, complex algorithms and new types of AI-based markers, such as meta-biomarkers, are emerging by integrating multimodal/multi-omics data.

CONCLUSION

AI-based methods have expanded the horizon for biomarker discovery, demonstrating the power of integrating multimodal data from existing datasets to discover new meta-biomarkers. While most of the included studies showed promise for AI-based prediction of benefit from immunotherapy, none provided high-level evidence for immediate practice change. A priori planned prospective trial designs are needed to cover all lifecycle steps of these software biomarkers, from development and validation to integration into clinical practice.

Revolutionizing cancer drug development: Harnessing the potential of basket trials

The landscape of cancer therapy has been transformed by advances in clinical next-generation sequencing, genomically targeted therapies, and immunotherapies. Well designed clinical trials and efficient clinical trial conduct are crucial for advancing our understanding of cancer, improving patient outcomes, and identifying personalized treatments. Basket trials have emerged as one of the efficient modern clinical trial designs that evaluate the efficacy of these therapies across multiple cancer types based on specific molecular alterations or biomarkers, irrespective of histology or anatomic location. This review delves into the evolution of basket trials in cancer drug development, highlighting their potential prospects and current obstacles. The design of basket trials involves screening patients for specific molecular alterations or biomarkers and enrolling them in the trial to receive the targeted therapy under investigation. Statistical considerations play a crucial role in the design, analysis, and interpretation of basket trials. Several notable examples of basket trials that have led to US Food and Drug Administration approval for uncommon molecular alterations (e.g., NTRK fusions, BRAF mutations, RET and FGFR1 alterations) are discussed, including LOXO-TRK (ClinicalTrials.gov identifier NCT02122913)/SCOUT (ClinicalTrials.gov identifier NCT02637687)/NAVIGATE (ClinicalTrials.gov identifier NCT02576431)/STARTRK (ClinicalTrials.gov identifiers NT02097810, NT02568267), VE-BASKET (ClinicalTrials.gov identifier NCT01524978), ROAR Basket (ClinicalTrials.gov identifier NCT02034110), LIBRETTO-001 (ClinicalTrials.gov identifier NCT03157128), ARROW (ClinicalTrials.gov identifier NCT03037385), FIGHT-203 (ClinicalTrials.gov identifier NCT03011372), and the National Cancer Institute-Molecular Analysis for Therapy Choice trial (ClinicalTrials.gov identifier NCT02465060). Basket trials have the potential to revolutionize cancer treatment by identifying effective therapies for patients based on specific molecular alterations or biomarkers rather than traditional histology-based approaches. PLAIN LANGUAGE SUMMARY: To gain more knowledge about cancer, improve patient outcomes, and discover personalized treatments, it is crucial to conduct clinical trials efficiently. One effective type of clinical trial is called a basket trial. In basket trials, new treatments are tested on various types of cancer, regardless of their location in the body; instead, researchers focus on specific abnormalities in the cancer cells. Basket trials offer hope that we can find personalized treatments that are more effective for each individual battling cancer.

Identifying survival of pan-cancer patients under immunotherapy using genomic mutation signature with large sample cohorts

Although immune checkpoint inhibitors have led to durable clinical response in multiple cancers, only a small proportion of patients respond to this treatment. Therefore, we aim to develop a predictive model that utilizes gene mutation profiles to accurately identify the survival of pan-cancer patients with immunotherapy. Here, we develop and evaluate three different nomograms using two cohorts containing 1,594 cancer patients whose mutation profiles are obtained by MSK-IMPACT sequencing and 230 cancer patients receiving whole-exome sequencing, respectively. Using eighteen genes (SETD2, BRAF, NCOA3, LATS1, IL7R, CREBBP, TET1, EPHA7, KDM5C, MET, KMT2D, RET, PAK7, CSF1R, JAK2, FAT1, ASXL1 and SPEN), the first nomogram stratifies patients from both cohorts into High-Risk and Low-Risk groups. Pan-cancer patients in the High-Risk group exhibit significantly shorter overall survival and progression-free survival than patients in the Low-Risk group in both cohorts. Meanwhile, the first nomogram also accurately identifies the survival of patients with melanoma or lung cancer undergoing immunotherapy, or pan-cancer patients treated with anti-PD-1/PD-L1 inhibitor or anti-CTLA-4 inhibitor. The model proposed is not a prognostic model for the survival of pan-cancer patients without immunotherapy, but a simple, effective and robust predictive model for pan-cancer patients' survival under immunotherapy, and could provide valuable assistance for clinical practice.

Restriction site associated DNA sequencing for tumour mutation burden estimation and mutation signature analysis

BACKGROUND

Genome-wide measures of genetic disruption such as tumour mutation burden (TMB) and mutation signatures are emerging as useful biomarkers to stratify patients for treatment. Clinicians commonly use cancer gene panels for tumour mutation burden estimation, and whole genome sequencing is the gold standard for mutation signature analysis. However, the accuracy and cost associated with these assays limits their utility at scale.

METHODS

WGS data from 560 breast cancer patients was used for in silico library simulations to evaluate the accuracy of an FDA approved cancer gene panel as well as restriction enzyme associated DNA sequencing (RADseq) libraries for TMB estimation and mutation signature analysis. We also transfected a mouse mammary cell line with APOBEC enzymes and sequenced resulting clones to evaluate the efficacy of RADseq in an experimental setting.

RESULTS

RADseq had improved accuracy of TMB estimation and derivation of mutation profiles when compared to the FDA approved cancer panel. Using simulated immune checkpoint blockade (ICB) trials, we show that inaccurate TMB estimation leads to a reduction in power for deriving an optimal TMB cutoff to stratify patients for immune checkpoint blockade treatment. Additionally, prioritisation of APOBEC hypermutated tumours in these trials optimises TMB cutoff determination for breast cancer. The utility of RADseq in an experimental setting was also demonstrated, based on characterisation of an APOBEC mutation signature in an APOBEC3A transfected mouse cell line.

CONCLUSION

In conclusion, our work demonstrates that RADseq has the potential to be used as a cost-effective, accurate solution for TMB estimation and mutation signature analysis by both clinicians and basic researchers.

The Landscape of Alterations from 1407 Ultra-Rare Sarcomas from the AACR GENIE Database: Clinical Implications

PURPOSE

Ultra-rare sarcomas (URS) comprise a group of orphan diseases with an incidence of ≤1/1,000,000 people per year. We aimed to assess clinically actionable genomic alterations in URS.

EXPERIMENTAL DESIGN

Data were extracted from the GENIE database using cBioPortal. OncoKB was used to assess for clinical actionability of mutations. Tumor mutational burden (TMB) was inferred from clinical sequencing data.

RESULTS

Soft tissue (ST) URS made up 23.5% of ST sarcoma cases, and bone URS made up 16.5% of bone sarcoma cases. The most commonly mutated gene in all four groups was TP53. The most common fusions involved EWSR1. The most common copy-number variations included deletions of CDKN2A and CDKN2B and amplifications of MDM2 and CDK4. TMB was generally low across all four categories of sarcoma, though there was considerable heterogeneity, with 3.8% of ST URS and 0.55% of bone URS having high TMB. We find Level 1 alterations (FDA-recognized biomarker predictive of response to an FDA-approved drug) in 10.0% of ST URS compared with 7.1% of ST non-URS, 1.1% of bone URS, and 4.5% of bone non-URS. Level 1-3 alterations (also include alterations for which there are standard-of-care drugs or clinical evidence supporting a drug) were seen in 27.8% of ST URS, 25.2% of ST non-URS, 20.9% of bone URS, and 17.4% of bone non-URS.

CONCLUSIONS

Clinically actionable genomic alterations are seen in a substantial fraction of URS. Clinical sequencing in advanced URS has the potential to guide the treatment of a significant portion of patients with URS.

NOTCH1 and PIK3CA mutation are related to HPV-associated vulvar squamous cell carcinoma

NOTCH1 and PIK3CA are members of important cell signalling pathways that are deregulated in squamous cell carcinomas of various organs. Vulvar squamous cell carcinomas (vulvSCC) are classically divided into two pathways, HPV-associated or HPV-independent, but the effect of NOTCH1 and PIK3CA mutations in both groups is unclear. We analysed two different cohorts of vulvSCC using Hybrid Capture-based Comprehensive Genomic Profiling and identified NOTCH1 and PIK3CA mutations in 35% and 31% of 48 primary vulvSCC. In this first cohort, PIK3CA and NOTCH1 mutations were significantly correlated with HPV infection (p < 0.01). Furthermore, mutations in both genes were associated with an advanced tumor stage and poorly differentiated status (p < 0.05). PIK3CA and NOTCH1 mutations were also associated with shorter patient survival which did not reach significance. In the second cohort of 735 advanced vulvSCC from metastatic site biopsies or from sites of unresectable loco-regional disease, NOTCH1 and PIK3CA mutations were reported in 14% and 20.3%, respectively. 4 of 48 (8%) and 22 of 735 vulvSCC (3.0%) featured genomic alterations (short variants and/or copy number changes and/or rearrangements) in both NOTCH1 and PIK3CA. NOTCH1 mutations were mostly located in the extracellular EGF-like domains, were inactivating and indicated that NOTCH1 functions predominantly as a tumor suppressor gene in vulvSCC. In contrast, PIK3CA mutations favored hotspot codons 1624 and 1633 of the gene, indicating that PIK3CA acts as an oncogene in vulvar carcinogenesis. In conclusion, NOTCH1 and PIK3CA mutations are detectable in a substantial proportion of vulvSCC and are related to HPV infection and more aggressive tumor behaviour.

Emerging Prognostic and Predictive Factors in Pancreatic Cancer

Pancreatic cancer is a lethal disease with increasing incidence and high recurrence rates and is currently resistant to conventional therapies. Moreover, it displays extensive morphologic and molecular intratumoral and intertumoral heterogeneity and a mostly low mutational burden, failing to induce significant antitumor immunity. Thus, immunotherapy has shown limited effect in pancreatic cancer, except in rare tumors with microsatellite instability, constituting <1% of the cases. Currently, new methods, including single-cell and single-nucleus RNA sequencing, have refined and expanded the 2-group molecular classification based on bulk RNA sequencing (classical and basal-like subtypes), identifying hybrid forms and providing us with a comprehensive map of the tumor cell subsets that drive gene expression during tumor evolution, simultaneously giving us insight into therapy resistance and metastasis. Additionally, deeper profiling of the tumor microenvironment of pancreatic cancer by using spatial analyses and multiplex imaging techniques has improved our understanding of the heterogeneous distribution of both adaptive and innate immune components with their protumor and antitumor properties. By integrating host immune response patterns, as defined by spatial transcriptomic and proteomic analysis and multiplex immunofluorescence, with molecular and morphologic features of the tumors, we can increasingly understand the genetic, immunologic, and morphologic background of pancreatic cancer and recognize the potential predictors for different treatment modalities.

Comprehensive genomic characterization of sporadic synchronous colorectal cancer: Implications for treatment optimization and clinical outcome

Sporadic synchronous colorectal cancer (SCRC) refers to multiple primary CRC tumors detected simultaneously in an individual without predisposing hereditary conditions, which accounts for the majority of multiple CRCs while lacking a profound understanding of the genomic landscape and evolutionary dynamics to optimize its treatment. In this study, 103 primary tumor samples from 51 patients with SCRC undergo whole-exome sequencing. The germline and somatic mutations and evolutionary and clinical features are comprehensively investigated. Somatic genetic events are largely inconsistent between paired tumors. Compared with solitary CRC, SCRCs have higher prevalence of tumor mutation burden high (TMB-H; 33.3%) and microsatellite-instability high (MSI-H; 29.4%) and different mutation frequencies in oncogenic signaling pathways. Moreover, neutrally evolving SCRC tumors are associated with higher intratumoral heterogeneity and better prognosis. These findings unveil special molecular features, carcinogenesis, and prognosis of sporadic SCRC. Strategies for targeted therapy and immunotherapy should be optimized accordingly.

Hot and cold tumors: Immunological features and the therapeutic strategies

The "hotness" or "coldness" of the tumors are determined by the information of the cancer cells themselves, tumor immune characteristics, tumor microenvironment, and signaling mechanisms, which are key factors affecting cancer patients' clinical efficacy. The switch mechanism of "hotness" and "coldness" and its corresponding pathological characteristics and treatment strategies are the frontier and hot spot of tumor treatment. How to distinguish the "hotness" or "coldness" effectively and clarify the causes, microenvironment state, and characteristics are very important for the tumor response and efficacy treatments. Starting from the concept of hot and cold tumor, this review systematically summarized the molecular characteristics, influencing factors, and therapeutic strategies of "hot and cold tumors," and analyzed the immunophenotypes, the tumor microenvironment, the signaling pathways, and the molecular markers that contribute to "hot and cold tumors" in details. Different therapeutic strategies for "cold and hot tumors" based on clinical efficacy were analyzed with drug targets and proteins for "cold and hot tumors." Furthermore, this review combines the therapeutic strategies of different "hot and cold tumors" with traditional medicine and modern medicine, to provide a basis and guidance for clinical decision-making of cancer treatment.

Mutational spectrum of TP53 gene correlates with nivolumab treatment efficacy in advanced gastric cancer (TP53MUT study)

BACKGROUND

Although nivolumab has a high efficacy, reliable biomarkers are needed to predict the efficacy. We evaluated the nivolumab efficacy according to the TP53 mutation in advanced gastric cancer patients enrolled in the GI-SCREEN project.

METHODS

Sequence data of tumour specimens and clinicopathological information of 913 patients with advanced gastric cancer who were enrolled between April 2015 and March 2017 were obtained from the GI-SCREEN database. The follow-up information of 266 patients treated with nivolumab was also provided.

RESULTS

Among 266 patients treated with nivolumab, the objective response rate (ORR) of TP53 wild type (wt) patients (24.6%) was higher than that of TP53 mutant patients (14.8%). Among TP53 mutant patients, the ORR of the frameshift type tended to be higher than the transition and transversion type (23.1%, 13.6%, and 13.0%, respectively). The median progression-free survival (PFS) was statistically longer in TP53 wt patients than in mutant patients (3.3 vs 2.1 months, HR 1.4, 95% CI 1.1-1.9). Among TP53 mutant patients, PFS was statistically longer in the frameshift type than in the transversion type.

CONCLUSION

Nivolumab showed better efficacy in TP53 wt patients than in mutant patients. Among TP53 mutant patients, the frameshift type may have efficacy from nivolumab treatment.

Reuniting philosophy and science to advance cancer research

Cancers rely on multiple, heterogeneous processes at different scales, pertaining to many biomedical fields. Therefore, understanding cancer is necessarily an interdisciplinary task that requires placing specialised experimental and clinical research into a broader conceptual, theoretical, and methodological framework. Without such a framework, oncology will collect piecemeal results, with scant dialogue between the different scientific communities studying cancer. We argue that one important way forward in service of a more successful dialogue is through greater integration of applied sciences (experimental and clinical) with conceptual and theoretical approaches, informed by philosophical methods. By way of illustration, we explore six central themes: (i) the role of mutations in cancer; (ii) the clonal evolution of cancer cells; (iii) the relationship between cancer and multicellularity; (iv) the tumour microenvironment; (v) the immune system; and (vi) stem cells. In each case, we examine open questions in the scientific literature through a philosophical methodology and show the benefit of such a synergy for the scientific and medical understanding of cancer.

Integrating angiogenesis signature and tumor mutation burden for improved patient stratification in immune checkpoint blockade therapy for muscle-invasive bladder cancer

BACKGROUND

Muscle-invasive bladder cancer (MIBC) patients have benefitted greatly from immune checkpoint blockade (ICB) therapy. However, there is a pressing need to identify factors underlying the heterogeneity of clinical responses to ICB.

METHODS

We conducted a study on 848 MIBC patients from 4 independent cohorts to investigate the key biological characteristics affecting ICB responses. The IMvigor210 cohort (n = 234) was used to identify the key factor, followed by exploration of the correlation between tumor angiogenesis and immune suppression in the IMvigor210, TCGA (n = 391), and UNC-108 (n = 89) cohorts. The ZSHS cohort (n = 134) was used for validation. Additionally, we integrated angiogenesis signature with tumor mutation burden (TMB) to decipher the heterogeneity of clinical outcomes to ICB in MIBC patients.

RESULTS

Our analysis revealed that nonresponders to PD-L1 blockade were enriched with angiogenesis signature. Furthermore, we observed a correlation between angiogenesis signature and decreased neoantigen load, downregulated T-cell antigen recognition, and noninflamed immunophenotype. We identified a subgroup of patients resistant to ICB, characterized by high angiogenesis signature and low tumor mutation burden (TMB), and found the activation of TGF-β signaling and downregulation of T-cell cytolytic signatures in this subgroup.

CONCLUSIONS

The study concluded that angiogenesis signature is closely associated with an immunosuppressive microenvironment, leading to resistance to ICB therapy in MIBC patients. The study further suggested that the combination of angiogenesis signature and TMB can serve as an integrated biomarker for better stratification of patients' clinical outcomes to ICB therapy.

Biomarkers for Immunotherapy in Driver-Gene-Negative Advanced NSCLC

Outcome improvement in patients with driver-gene-negative advanced non-small cell lung cancer (NSCLC) has been significantly enhanced through targeting the immune system, specifically the PD-L1/PD-1 axis. Nevertheless, only a subset of patients with advanced NSCLC may derive benefits from immuno-monotherapy or immunotherapy combined with chemotherapy. Hence, in order to identify patients who will gain the maximum advantage from immunotherapy, it is crucial to investigate predictive biomarkers. This review provides a summary of the currently identified biomarkers associated with the extent of benefit from immuno-monotherapy or immunotherapy combined with chemotherapy in patients with advanced NSCLC. These biomarkers can be categorized into three groups: tumor-related, tumor-microenvironment-related, and host-factor-related.Tumor-related factors include PD-L1 expression, tumor mutational burden and specific genetic mutations, while tumor-microenvironment-related factors include extracellular vesicles and T-cell receptors, and host-related factors include systemic inflammation, circulating fatty acid profile, and the microbiome.

Gene-network analysis predicts clinical response to immunotherapy in patients affected by NSCLC

OBJECTIVES

Predictive biomarkers of response to immune checkpoint inhibitors (ICIs) have been extensively studied in non-small cell lung cancer (NSCLC) with controversial results. Recently, gene-network analysis emerged as a new tool to address tumor biology and behavior, representing a potential tool to evaluate response to therapies.

METHODS

Clinical data and genetic profiles of 644 advanced NSCLCs were retrieved from cBioPortal and the Cancer Genome Atlas (TCGA); 243 ICI-treated NSCLCs were used to identify an immunotherapy response signatures via mutated gene network analysis and K-means unsupervised clustering. Signatures predictive values were tested in an external dataset of 242 cases and assessed versus a control group of 159 NSCLCs treated with standard chemotherapy.

RESULTS

At least two mutations in the coding sequence of genes belonging to the chromatin remodelling pathway (A signature), and/or at least two mutations of genes involved in cell-to-cell signalling pathways (B signature), showed positive prediction in ICI-treated advanced NSCLC. Signatures performed best when combined for patients undergoing first-line immunotherapy, and for those receiving combined ICIs.

CONCLUSIONS

Alterations in genes related to chromatin remodelling complexes and cell-to-cell crosstalk may force dysfunctional immune evasion, explaining susceptibility to immunotherapy. Therefore, exploring mutated gene networks could be valuable for determining essential biological interactions, contributing to treatment personalization.

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

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

Correlation between biomarkers and treatment outcomes in diverse cancers: a systematic review and meta-analysis of phase I and II immunotherapy clinical trials

BACKGROUND

Many immuno-oncology (IO) trials are conducted without biomarker selection. We performed a meta-analysis of phase I/II clinical trials evaluating immune checkpoint inhibitors (ICIs) to determine the association between biomarkers and clinical outcomes, if any.

METHODS

A PubMed search for phase I/II clinical trials with drugs approved by the Food and Drug Administration (labelled, off-label, combined with investigational ICIs or other treatment modalities) from 2018 to 2020 was performed. The objective response rate (ORR), progression-free survival (PFS) and overall survival (OS) were compared between biomarker-positive and biomarker-negative groups, using studies that explored the correlation of biomarkers with outcomes.

RESULTS

Overall, 174 clinical studies that included 19,178 patients were identified, and 132 studies investigated>30 correlative biomarkers that included PD-L1 expression (≥1%, 111 studies), tumour mutational burden (20 studies) and microsatellite instability/mismatch repair deficiency (10 studies). Overall, 123, 46 and 30 cohorts (drugs, tumour types or biomarkers) with 11,692, 3065, and 2256 patient outcomes for ORR, PFS and OS, respectively, were analysed in correlation with biomarkers. Meta-analyses demonstrated that ICIs in patients with biomarker-positive tumours were associated with higher ORR (odds ratio 2.15 [95% CI, 1.79-2.58], p < 0.0001); and longer PFS (hazard ratio [HR] 0.55 [95% CI, 0.45-0.67], p < 0.0001), and OS (HR 0.65 [95% CI, 0.53-0.80], p < 0.0001) compared with those with biomarker-negative tumours. Significance for ORR and PFS was retained in multivariate analysis (p < 0.001) (OS, not included owing to the small number of trials reporting OS).

CONCLUSION

Our data suggest that IO biomarkers should be used in patient selection for ICIs. Prospective studies are warranted.

Mitochondrial DNA methylation is a predictor of immunotherapy response and prognosis in breast cancer: scRNA-seq and bulk-seq data insights

Background

Alterations in Mitochondrial DNA methylation (MTDM) exist in many tumors, but their role in breast cancer (BC) development remains unclear.

Methods

We analyzed BC patient data by combining scRNA-seq and bulk sequencing. Weighted co-expression network analysis (WGCNA) of TCGA data identified mitochondrial DNA methylation (MTDM)-associated genes in BC. COX regression and LASSO regression were used to build prognostic models. The biological function of MTDM was assessed using various methods, such as signaling pathway enrichment analysis, copynumber karyotyping analysis, and quantitative analysis of the cell proliferation rate. We also evaluated MTDM-mediated alterations in the immune microenvironment using immune microenvironment, microsatellite instability, mutation, unsupervised clustering, malignant cell subtype differentiation, immune cell subtype differentiation, and cell-communication signature analyses. Finally, we performed cellular experiments to validate the role of the MTDM-associated prognostic gene NCAPD3 in BC.

Results

In this study, MTDM-associated prognostic models divided BC patients into high/low MTDM groups in TCGA/GEO datasets. The difference in survival time between the two groups was statistically significant (P<0.001). We found that high MTDM status was positively correlated with tumor cell proliferation. We analyzed the immune microenvironment and found that low-MTDM group had higher immune checkpoint gene expression/immune cell infiltration, which could lead to potential benefits from immunotherapy. In contrast, the high MTDM group had higher proliferation rates and levels of CD8+T cell exhaustion, which may be related to the secretion of GDF15 by malignant breast epithelial cells with a high MTDM status. Cellular experiments validated the role of the MTDM-associated prognostic gene NCAPD3 (the gene most positively correlated with epithelial malignant cell proliferation in the model) in BC. Knockdown of NCAPD3 significantly reduced the activity and proliferation of MDA-MB-231 and BCAP-37 cells, and significantly reduced their migration ability of BCAP-37 cell line.

Conclusion

This study presented a holistic evaluation of the multifaceted roles of MTDM in BC. The analysis of MTDM levels not only enables the prediction of response to immunotherapy but also serves as an accurate prognostic indicator for patients with BC. These insightful discoveries provide novel perspectives on tumor immunity and have the potentially to revolutionize the diagnosis and treatment of BC.

Novel Genetic Subtypes of Urothelial Carcinoma With Differential Outcomes on Immune Checkpoint Blockade

PURPOSE

Immune checkpoint blockade (ICB) therapy has significantly improved clinical outcomes in bladder cancer. Identification of correlates of benefit is critical to select appropriate therapy for individual patients.

METHODS

To reveal genetic variables associated with benefit from ICB, we performed whole-exome sequencing on tumor specimens from 88 patients with advanced bladder cancer treated with ICB.

RESULTS

We identified several genetic factors that correlated with progression-free and overall survival after ICB therapy including ARID1A mutation, tumor mutational burden, intratumoral heterogeneity, the ratio of nonsynonymous to synonymous mutations in the immunopeptidome (immune dN/dS), and tumor cell purity. In addition, we noted that neutrophil-to-lymphocyte ratio and smoking history were negatively associated with overall survival. These genetic characteristics define four molecular subtypes demonstrating differential sensitivity to ICB. We validated the association of these four subtypes with clinical benefit from ICB in an independent cohort (IMvigor210). Finally, we showed that these molecular subtypes also correlate with outcome, although with distinct relationships, among patients not treated with ICB using The Cancer Genome Atlas (TCGA) bladder cancer cohort. Using parallel RNA sequencing data, the subtypes were also shown to correlate with immune infiltration and inflammation, respectively, in the IMvigor210 and TCGA cohorts.

CONCLUSION

Together, our study defines molecular subgroups of bladder cancer that influence benefit from ICB.

Universal cutoff for tumor mutational burden in predicting the efficacy of anti-PD-(L)1 therapy for advanced cancers

Background: The US Food and Drug Administration (FDA)'s tumor-agnostic approval of pembrolizumab in high tumor mutational burden (TMB-high, i.e., TMB≥10 mut/Mb) cases, based on the data from KEYNOTE-158, has raised considerable concerns among the immuno-oncology community. This study aims to statistically infer the optimal universal cutoff in defining TMB-high that is predictive of the efficacy of anti-PD-(L) 1 therapy in advanced solid tumors. Methods: We integrated MSK-IMPACT TMB data from a public cohort and the objective response rate (ORR) for anti-PD-(L) 1 monotherapy across diverse cancer types in published trials. The optimal TMB cutoff was determined by varying the universal cutoff to define TMB-high across cancer types and examining the cancer-level correlation between objective response rate and the proportion of TMB-high cases. The utility of this cutoff in predicting overall survival (OS) benefits from anti-PD-(L) 1 therapy was then evaluated in a validation cohort of advanced cancers with coupled MSK-IMPACT TMB and OS data. In silico analysis of whole-exome sequencing data from The Cancer Genome Atlas was further employed to assess the generalizability of the identified cutoff among panels comprising several hundred genes. Results: The cancer type-level analysis identified 10 mut/Mb as the optimal cutoff for MSK-IMPACT in defining TMB-high, with the corresponding TMB-high (TMB≥10 mut/Mb) percentage strongly correlated with ORR for PD-(L) 1 blockade across cancer types [correlation coefficient, 0.72 (95% CI, 0.45-0.88)]. This cutoff was also the optimum in defining TMB-high (via MSK-IMPACT) when predicting OS benefits from anti-PD-(L) 1 therapy in the validation cohort. In this cohort, TMB≥10 mut/Mb was associated with significantly improved OS (hazard ratio, 0.58 [95% CI, 0.48-0.71]; p < 0.001). Moreover, in silico analyses revealed excellent agreement of TMB≥10 mut/Mb cases between MSK-IMPACT and the FDA-approved panels and between MSK-IMPACT and various randomly sampled panels. Conclusion: Our study demonstrates that 10 mut/Mb is the optimal, universal cutoff for TMB-high that guides the clinical application of anti-PD-(L) 1 therapy for advanced solid tumors. It also provides rigorous evidence beyond KEYNOTE-158 for the utility of TMB≥10 mut/Mb in predicting the efficacy of PD-(L) 1 blockade in broader settings, which could help to mitigate the challenges in embracing the tumor-agnostic approval of pembrolizumab in TMB-high cases.

What makes TMB an ambivalent biomarker for immunotherapy? A subtle mismatch between the sample-based design of variant callers and real clinical cohort

Tumor mutation burden (TMB) is a widely recognized biomarker for predicting the efficacy of immunotherapy. However, its use still remains highly controversial. In this study, we examine the underlying causes of this controversy based on clinical needs. By tracing the source of the TMB errors and analyzing the design philosophy behind variant callers, we identify the conflict between the incompleteness of biostatistics rules and the variety of clinical samples as the critical issue that renders TMB an ambivalent biomarker. A series of experiments were conducted to illustrate the challenges of mutation detection in clinical practice. Additionally, we also discuss potential strategies for overcoming these conflict issues to enable the application of TMB in guiding decision-making in real clinical settings.

Identification of CircRNA signature associated with tumor immune infiltration to predict therapeutic efficacy of immunotherapy

Circular RNAs (circRNAs) play important roles in the regulation of cancer. However, the clinical implications and regulatory networks of circRNAs in cancer patients receiving immune checkpoint blockades (ICB) have not been fully elucidated. Here, we characterize circRNA expression profiles in two independent cohorts of 157 ICB-treated advanced melanoma patients and reveal overall overexpression of circRNAs in ICB non-responders in both pre-treatment and early during therapy. Then, we construct circRNA-miRNA-mRNA regulatory networks to reveal circRNA-related signaling pathways in the context of ICB treatment. Further, we construct an ICB-related circRNA signature (ICBcircSig) score model based on progression-free survival-related circRNAs to predict immunotherapy efficacy. Mechanistically, the overexpression of ICBcircSig circTMTC3 and circFAM117B could increase PD-L1 expression via the miR-142-5p/PD-L1 axis, thus reducing T cell activity and leading to immune escape. Overall, our study characterizes circRNA profiles and regulatory networks in ICB-treated patients, and highlights the clinical utility of circRNAs as predictive biomarkers of immunotherapy.

Current Progress on Predictive Biomarkers for Response to Immune Checkpoint Inhibitors in Gastric Cancer: How to Maximize the Immunotherapeutic Benefit?

Gastric cancer is the fifth most prevalent cancer and the fourth leading cause of cancer death globally. Delayed diagnosis and pronounced histological and molecular variations increase the complexity and challenge of treatment. Pharmacotherapy, which for a long time was systemic chemotherapy based on 5-fluorouracil, is the mainstay of management for advanced gastric cancer. Trastuzumab and programmed cell death 1 (PD-1) inhibitors have altered the therapeutic landscape, contributing to noticeably prolonged survivorship in patients with metastatic gastric cancer. However, research has revealed that immunotherapy is only beneficial to some individuals. Biomarkers, such as programmed cell death ligand 1 (PD-L1), microsatellite instability (MSI), and tumor mutational load (TMB), have been shown to correlate with immune efficacy in numerous studies and are increasingly employed for the selection of patients most likely to respond to immunotherapy. Gut microorganisms, genetic mutations like POLE/POLD1 and NOTCH4, tumor lymphoid infiltrating cells (TILs), and other novel biomarkers have the potential to develop into new predictors. Prospective immunotherapy for gastric cancer should be guided by a biomarker-driven precision management paradigm, and multidimensional or dynamic marker testing could be the way to go.

Precision Oncology Targets in Biliary Tract Cancer

Targeted therapies in biliary tract cancer (BTC) are emerging as options for patients not who do not respond to first-line treatment. Agents acting on tumor-specific oncogenes in BTC may target fibroblast growth factor receptor 2 (FGFR2), isocitrate dehydrogenase (IDH), B-raf kinase (BRAF), and human epidermal growth factor receptor 2 (HER-2). Additionally, given the heterogeneous genetic landscape of advanced BTCs, many harbor genetic aberrations that are common among solid tumors, including RET fusions, tropomyosin receptor kinase (TRK) fusions, and high tumor mutational burden (TMB). This review aims to provide updates on the evolving array of therapeutics available, and to summarize promising works on the horizon.

Tumor grade-associated genomic mutations in Chinese patients with non-small cell lung cancer

Background

Lung cancer is the most prevalent cancer worldwide and accounts for approximately 20% of cancer-related death in China every year. High-grade lung cancer poses a significant threat to patients, and developing a novel treatment for these patients requires an understanding of its underlying mechanism.

Methods

Chinese patients with lung cancer were enrolled. The tumor samples were collected by surgery or puncture and applied for next-generation sequencing. A panel of pan-cancer genes was targeted, and the sequencing depth was set to over 1,000 to improve the sensitivity of detecting mutations. Short-length mutations (substitution, insertion, and deletion), copy number variation, and gene fusion were called. Gene mutations were compared between low-grade, middle-grade, and high-grade tumors using Fisher's exact test. The enriched pathways in each grade of tumors were also inferred.

Results

The study included 173 Chinese patients with non-small cell lung cancer, of whom 98 (56.6%) patients were female and 75 (43.4%) were male, with a mean age of 56.8 years. All patients were microsatellite stable; 66.4% were at the early stages (Stages 0, I, and II) with a tumor mutational burden of approximately 2.5 (confidence interval = [0, 48.3]). Compared to low-grade tumors, high-grade tumors had a significantly higher percentage of mutations in TP53 (75.9% vs 34.4%, p = 1.86e-3) and PIK3CA (24.1% vs. 0%, p = 3.58e-3). Pathway analysis found that high-grade tumors were enriched with mutations in bacterial invasion of epithelial cells (31% vs. 0%, p = 5.8e-4), Epstein-Barr virus infection (79.3% vs. 37.5%, p = 1.72e-3), and the Wnt signaling pathway (75.9% vs. 34.4%, p = 1.91e-3). High-grade tumors had a significantly higher tumor mutational burden than low-grade tumors (p-value = 0.0017). However, actionable mutations with high-level evidence were lower in high-grade tumors.

Conclusion

Patients with high-grade tumors from lung cancer may be more affected by bacteria and Epstein-Barr virus than low-grade tumors. High-grade tumors were specially mutated in TP53 and PIK3CA and may benefit more from immunotherapy. Further research on the underlying mechanism of high-grade lung cancer is necessary to develop new therapeutic options. Lung cancer, tumor grade, genomic mutations, Epstein-Barr virus, pathway analysis.