Ancestry-driven recalibration of tumor mutational burden and disparate clinical outcomes in response to immune checkpoint inhibitors

Preclinical in vitro models of HNSCC and their role in drug discovery - an emphasis on the cancer microenvironment and microbiota

INTRODUCTION

Head and neck squamous cell carcinoma (HNSCC) is the seventh most common cancer worldwide. Treatment options and patient outcomes have not improved significantly over the past decades, increasing the need for better preclinical models. Holistic approaches that include an intact and functional immune compartment along with the patient's individual tumor microbiome will help improve the predictive value of novel drug efficacy.

AREAS COVERED

In this review, we describe the challenges of modeling the complex and heterogeneous tumor landscape in HNSCC and the importance of sophisticated patient-specific 3D in vitro models to pave the way for clinical trials with novel immunomodulatory drugs. We also discuss the impact of the tumor microbiome and the potential implications for prospective drug screening and validation trials.

EXPERT OPINION

The repertoire of well-characterized preclinical 3D in vitro models continues to grow. With the increasing attention to the complex cellular, immunological, molecular, and spatio-temporal characteristics of tumors, well-designed proof-of-concept studies to test novel drug efficacy are on the verge of providing valuable, practice-changing insights for clinical trials. Bringing together expertise and improving collaboration between clinicians, academics, and regulatory agencies will facilitate the translation of preclinical findings into clinically meaningful outcomes.

Improving the efficacy of cancer immunotherapy by host-defence caerin 1.1 and 1.9 peptides

Cancer remains a major global health challenge. Immunotherapy has revolutionized the management of cancer, yet only a limited number of patients respond to such treatments. This is largely attributed to the immunosuppressive tumor microenvironment, which diminishes the effectiveness of immunotherapy. Recent studies have underscored the potential of naturally derived caerin 1 peptides, particularly caerin 1.1 and caerin 1.9, which exhibit strong antitumor effects and enhance the efficacy of immunotherapies in animal models. This review encapsulates the current research aimed at augmenting the effectiveness of immunotherapy, focusing on the role of caerin 1.1 and caerin 1.9 in boosting immunotherapeutic outcomes, elucidating possible mechanisms, and discussing their limitations and challenges.

Current trends in sensitizing immune checkpoint inhibitors for cancer treatment

Immune checkpoint inhibitors (ICIs) have dramatically transformed the treatment landscape for various malignancies, achieving notable clinical outcomes across a wide range of indications. Despite these advances, resistance to immune checkpoint blockade (ICB) remains a critical clinical challenge, characterized by variable response rates and non-durable benefits. However, growing research into the complex intrinsic and extrinsic characteristics of tumors has advanced our understanding of the mechanisms behind ICI resistance, potentially improving treatment outcomes. Additionally, robust predictive biomarkers are crucial for optimizing patient selection and maximizing the efficacy of ICBs. Recent studies have emphasized that multiple rational combination strategies can overcome immune checkpoint resistance and enhance susceptibility to ICIs. These findings not only deepen our understanding of tumor biology but also reveal the unique mechanisms of action of sensitizing agents, extending clinical benefits in cancer immunotherapy. In this review, we will explore the underlying biology of ICIs, discuss the significance of the tumor immune microenvironment (TIME) and clinical predictive biomarkers, analyze the current mechanisms of resistance, and outline alternative combination strategies to enhance the effectiveness of ICIs, including personalized strategies for sensitizing tumors to ICIs.

Single-nucleus chromatin accessibility and transcriptomic map of breast tissues of women of diverse genetic ancestry

Single-nucleus analysis allows robust cell-type classification and helps to establish relationships between chromatin accessibility and cell-type-specific gene expression. Here, using samples from 92 women of several genetic ancestries, we developed a comprehensive chromatin accessibility and gene expression atlas of the breast tissue. Integrated analysis revealed ten distinct cell types, including three major epithelial subtypes (luminal hormone sensing, luminal adaptive secretory precursor (LASP) and basal-myoepithelial), two endothelial and adipocyte subtypes, fibroblasts, T cells, and macrophages. In addition to the known cell identity genes FOXA1 (luminal hormone sensing), EHF and ELF5 (LASP), TP63 and KRT14 (basal-myoepithelial), epithelial subtypes displayed several uncharacterized markers and inferred gene regulatory networks. By integrating breast epithelial cell gene expression signatures with spatial transcriptomics, we identified gene expression and signaling differences between lobular and ductal epithelial cells and age-associated changes in signaling networks. LASP cells and fibroblasts showed genetic ancestry-dependent variability. An estrogen receptor-positive subpopulation of LASP cells with alveolar progenitor cell state was enriched in women of Indigenous American ancestry. Fibroblasts from breast tissues of women of African and European ancestry clustered differently, with accompanying gene expression differences. Collectively, these data provide a vital resource for further exploring genetic ancestry-dependent variability in healthy breast biology.

ESMO Recommendations on clinical reporting of genomic test results for solid cancers

BACKGROUND

Genomic tumour profiling has a crucial role in the management of patients with solid cancers, as it helps selecting and prioritising therapeutic interventions based on prognostic and predictive biomarkers, as well as identifying markers of hereditary cancers. Harmonised approaches to interpret the results of genomic testing are needed to support physicians in their decision making, prevent inequalities in precision medicine and maximise patient benefit from available cancer management options.

METHODS

The European Society for Medical Oncology (ESMO) Translational Research and Precision Medicine Working Group assembled a group of international experts to propose recommendations for preparing clinical genomic reports for solid cancers. These recommendations aim to foster best practices in integrating genomic testing within clinical settings. After review of available evidence, several rounds of surveys and focused discussions were conducted to reach consensus on the recommendation statements. Only consensus recommendations were reported. Recommendation statements were graded in two tiers based on their clinical importance: level A (required to maintain common standards in reporting) and level B (optional but necessary to achieve ideal practice).

RESULTS

Genomics reports should present key information in a front page(s) followed by supplementary information in one or more appendices. Reports should be structured into sections: (i) patient and sample details; (ii) assay and data analysis characteristics; (iii) sample-specific assay performance and quality control; (iv) genomic alterations and their functional annotation; (v) clinical actionability assessment and matching to potential therapy indications; and (vi) summary of the main findings. Specific recommendations to prepare each of these sections are made.

CONCLUSIONS

We present a set of recommendations aimed at structuring genomics reports to enhance physician comprehension of genomic profiling results for solid cancers. Communication between ordering physicians and professionals reporting genomic data is key to minimise uncertainties and to optimise the impact of genomic tests in patient care.

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.

Integrated profile of tumor stage and mutational burden predicts disparate clinical responses to immune checkpoint inhibitors: A risk-benefit study

Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment, having demonstrated efficacy and leading to regulatory approvals of ICIs in cancers characterized by high tumor mutation burden (TMB). However, there remains a gap in determining their applicability and risk-benefit profile, across the broad spectrum of patients whose tumors harbor varying TMB levels across distinct tumor stages. By interrogating a large contemporary cohort comprised of 10,233 patients with a diagnosis of cancer across all tumor stages and TMB levels, this study revealed significantly improved overall survival (OS) following ICI therapy (P < .0001) in patients with a combination of ≥10 mut/Mb and stage IV disease. In contrast, ICI therapy is associated with markedly worse OS in patients with low TMB levels <10 mut/Mb and stages I, II, and III cancer. These findings highlight the critical interplay between TMB, tumor stage, and ICI treatment outcomes, underscoring the importance of integrating clinical and genetic characteristics in weighing the risk-benefit balance of ICI therapy. Although maximizing therapeutic benefits is crucial, it is equally important to identify and manage potential risks that may not be immediately apparent. This may require enrolling patients with less-severe or early-stage disease to enable long-term follow-up with effective clinical surveillance. By comprehensively evaluating the added benefit of improved treatment efficacy and the potential risk of adverse treatment outcome, a risk-benefit profile can optimize immunotherapy regimens, with profound implications for clinical decision-making and regulatory approvals of ICI.

The 30th Annual Prostate Cancer Foundation Scientific Retreat Report

BACKGROUND

The 30th Annual Prostate Cancer Foundation (PCF) Scientific Retreat was held at the Omni La Costa Resort in Carlsbad, CA, from October 26 to 28, 2023. A hybrid component was included for virtual attendees.

METHODS

The Annual PCF Scientific Retreat is a leading international scientific conference focused on pioneering, unpublished, and impactful studies across the spectrum of basic through clinical prostate cancer research, as well as research from related fields with significant potential for improving prostate cancer research and patient outcomes.

RESULTS

The 2023 PCF Retreat concentrated on key areas of research, including: (i) the biology of cancer stem cells and prostate cancer lineage plasticity; (ii) mechanisms of treatment resistance; (iii) emerging AI applications in diagnostic medicine; (iv) analytical and computational biology approaches in cancer research; (v) the role of nerves in prostate cancer; (vi) the biology of prostate cancer bone metastases; (vii) the contribution of ancestry and genomics to prostate cancer disparities; (viii) prostate cancer 3D genomics; (ix) progress in new targets and treatments for prostate cancer; (x) the biology and translational applications of tumor extracellular vesicles; (xi) updates from PCF TACTICAL Award teams; (xii) novel platforms for small molecule molecular glues and binding inhibitors; and (xiii) diversity, equity and inclusion strategies for advancing cancer care equity.

CONCLUSIONS

This meeting report summarizes the presentations and discussions from the 2023 PCF Scientific Retreat. We hope that sharing this information will deepen our understanding of current and emerging research and drive future advancements in prostate cancer patient care.

Ancestry and somatic profile predict acral melanoma origin and prognosis

Acral melanoma, which is not ultraviolet (UV)-associated, is the most common type of melanoma in several low- and middle-income countries including Mexico. Latin American samples are significantly underrepresented in global cancer genomics studies, which directly affects patients in these regions as it is known that cancer risk and incidence may be influenced by ancestry and environmental exposures. To address this, here we characterise the genome and transcriptome of 128 acral melanoma tumours from 96 Mexican patients, a population notable because of its genetic admixture. Compared with other studies of melanoma, we found fewer frequent mutations in classical driver genes such as BRAF, NRAS or NF1. While most patients had predominantly Amerindian genetic ancestry, those with higher European ancestry had increased frequency of BRAF mutations and a lower number of structural variants. These BRAF-mutated tumours have a transcriptional profile similar to cutaneous non-volar melanocytes, suggesting that acral melanomas in these patients may arise from a distinct cell of origin compared to other tumours arising in these locations. KIT mutations were found in a subset of these tumours, and transcriptional profiling defined three expression clusters; these characteristics were associated with overall survival. We highlight novel low-frequency drivers, such as SPHKAP, which correlate with a distinct genomic profile and clinical characteristics. Our study enhances knowledge of this understudied disease and underscores the importance of including samples from diverse ancestries in cancer genomics studies.

A consensus-based classification workflow to determine genetically inferred ancestry from comprehensive genomic profiling of patients with solid tumors

Disparities in cancer diagnosis, treatment, and outcomes based on self-identified race and ethnicity (SIRE) are well documented, yet these variables have historically been excluded from clinical research. Without SIRE, genetic ancestry can be inferred using single-nucleotide polymorphisms (SNPs) detected from tumor DNA using comprehensive genomic profiling (CGP). However, factors inherent to CGP of tumor DNA increase the difficulty of identifying ancestry-informative SNPs, and current workflows for inferring genetic ancestry from CGP need improvements in key areas of the ancestry inference process. This study used genomic data from 4274 diverse reference subjects and CGP data from 491 patients with solid tumors and SIRE to develop and validate a workflow to obtain accurate genetically inferred ancestry (GIA) from CGP sequencing results. We use consensus-based classification to derive confident ancestral inferences from an expanded reference dataset covering eight world populations (African, Admixed American, Central Asian/Siberian, European, East Asian, Middle Eastern, Oceania, South Asian). Our GIA calls were highly concordant with SIRE (95%) and aligned well with reference populations of inferred ancestries. Further, our workflow could expand on SIRE by (i) detecting the ancestry of patients that usually lack appropriate racial categories, (ii) determining what patients have mixed ancestry, and (iii) resolving ancestries of patients in heterogeneous racial categories and who had missing SIRE. Accurate GIA provides needed information to enable ancestry-aware biomarker research, ensure the inclusion of underrepresented groups in clinical research, and increase the diverse representation of patient populations eligible for precision medicine therapies and trials.

Integrated Identification and Immunotherapy Response Analysis of the Prognostic Signature Associated With m6A, Cuproptosis-Related, Ferroptosis-Related lncRNA in Endometrial Cancer

BACKGROUND

Endometrial cancer (EC) stands as the predominant gynecological malignancy impacting the female reproductive system on a global scale. N6-methyladenosine, cuproptosis- and ferroptosis-related biomarker is beneficial to the prognostic of tumor patients. Nevertheless, the correlation between m6A-modified lncRNAs and ferroptosis, copper-induced apoptosis in the initiation and progression of EC remains unexplored in existing literature.

AIMS

In this study, based on bioinformatics approach, we identified lncRNAs co-expressing with cuproptosis-, ferroptosis-, m6A- related lncRNAs from expression data of EC. By constructing the prognosis model in EC, we screened hub lncRNA signatures affecting prognosis of EC patients. Furthermore, the guiding value of m6A-modified ferroptosis-related lncRNA (mfrlncRNA) features was assessed in terms of prognosis, immune microenvironment, and drug sensitivity.

METHOD

Our research harnessed gene expression data coupled with clinical insights derived from The Cancer Genome Atlas (TCGA) collection. To forge prognostic models, we adopted five machine learning approaches, assessing their efficacy through C-index and time-independent ROC analysis. We pinpointed prognostic indicators using the LASSO Cox regression approach. Moreover, we delved into the biological and immunological implications of the discovered lncRNA prognostic signatures.

RESULTS

The survival rate for the low-risk group was markedly higher than that for the high-risk group, as evidenced by a significant log-rank test (p < 0.001). The LASSO Cox regression model yielded concordance indices of 0.76 for the training set and 0.77 for the validation set, indicating reliable prognostic accuracy. Enrichment analysis of gene functions linked the identified signature predominantly to endopeptidase inhibitor activity, highlighting the signature's potential implications. Additionally, immune function and drug density emphasized the importance of early diagnosis in EC.

CONCLUSION

Five hub lncRNAs in EC were identified through constructing the prognosis model. Those genes might be potential biomarkers to provide valuable reference for targeted therapy and prognostic assessment of EC.

Impact of Genetic Ancestry on T-cell Acute Lymphoblastic Leukemia Outcomes

The influence of genetic ancestry on biology, survival outcomes, and risk stratification in T-cell Acute Lymphoblastic Leukemia (T-ALL) has not been explored. Genetic ancestry was genomically-derived from DNA-based single nucleotide polymorphisms in children and young adults with T-ALL treated on Children's Oncology Group trial AALL0434. We determined associations of genetic ancestry, leukemia genomics and survival outcomes; co-primary outcomes were genomic subtype, pathway alteration, overall survival (OS), and event-free survival (EFS). Among 1309 patients, T-ALL molecular subtypes varied significantly by genetic ancestry, including increased frequency of genomically defined ETP-like, MLLT10, and BCL11B-activated subtypes in patients of African ancestry. In multivariable Cox models adjusting for high-risk subtype and pathways, patients of Admixed American ancestry had superior 5-year EFS/OS compared with European; EFS/OS for patients of African and European ancestry were similar. The prognostic value of five commonly altered T-ALL genes varied by ancestry - including NOTCH1 , which was associated with superior OS for patients of European and Admixed American ancestry but non-prognostic among patients of African ancestry. Furthermore, a published five-gene risk classifier accurately risk stratified patients of European ancestry, but misclassified patients of African ancestry. We developed a penalized Cox model which successfully risk stratified patients across ancestries. Overall, 80% of patients had a genomic alteration in at least one gene with differential prognostic impact by genetic ancestry. T-ALL genomics and prognostic associations of genomic alterations vary by genetic ancestry. These data demonstrate the importance of incorporating genetic ancestry into analyses of tumor biology for risk classification algorithms.

Molecularly guided therapy versus chemotherapy after disease control in unfavourable cancer of unknown primary (CUPISCO): an open-label, randomised, phase 2 study

BACKGROUND

Patients with unfavourable subset cancer of unknown primary (CUP) have a poor prognosis when treated with standard platinum-based chemotherapy. Whether first-line treatment guided by comprehensive genomic profiling (CGP) can improve outcomes is unknown. The CUPISCO trial was designed to inform a molecularly guided treatment strategy to improve outcomes over standard platinum-based chemotherapy in patients with newly diagnosed, unfavourable, non-squamous CUP. The aim of the trial was to compare the efficacy and safety of molecularly guided therapy (MGT) versus standard platinum-based chemotherapy in these patients. This was to determine whether the inclusion of CGP in the initial diagnostic work-up leads to improved outcomes over the current standard of care. We herein report the primary analysis.

METHODS

CUPISCO was a phase 2, prospective, randomised, open-label, active-controlled, multicentre trial done at 159 sites in 34 countries outside the USA. Patients with central eligibility review-confirmed disease (acceptable histologies included adenocarcinoma and poorly differentiated carcinoma) and an Eastern Cooperative Oncology Group performance status of 0 or 1, evaluated by CGP, who reached disease control after three cycles of standard first-line platinum-based chemotherapy were randomly assigned 3:1 via a block-stratified randomisation procedure to MGT versus chemotherapy continuation for at least three further cycles. The primary endpoint was investigator-assessed progression-free survival in the intention-to-treat population. The study is registered with ClinicalTrials.gov, NCT03498521, and follow-up is ongoing.

FINDINGS

From July 10, 2018, to Dec 9, 2022, 636 (42%) of 1505 screened patients were enrolled. Median follow-up in the treatment period was 24·1 months (IQR 11·6-35·6). Of 438 patients who reached disease control after induction chemotherapy, 436 were randomly assigned: 326 (75%) to the MGT group and 110 (25%) to the chemotherapy group. Median progression-free survival in the intention-to-treat population was 6·1 months (95% CI 4·7-6·5) in the MGT group versus 4·4 months (4·1-5·6) in the chemotherapy group (hazard ratio 0·72 [95% CI 0·56-0·92]; p=0·0079). Related adverse event rates per 100-patient-years at risk were generally similar or lower with MGT versus chemotherapy.

INTERPRETATION

In patients with previously untreated, unfavourable, non-squamous CUP who reached disease control after induction chemotherapy, CGP with subsequent MGTs resulted in longer progression-free survival than standard platinum-based chemotherapy. On the basis of these results, we recommend that CGP is performed at initial diagnosis in patients with unfavourable CUP.

FUNDING

F Hoffmann-La Roche.

Efficacy and Safety of Programmed Death 1/Programmed Death-Ligand 1 Plus Cytotoxic T-Lymphocyte-Associated Antigen 4 Inhibitors for Advanced or Metastatic Non-Small Cell Lung Cancer: A Meta-analysis Based on Randomized Controlled Trials

BACKGROUND

This meta-analysis aims to investigate the efficacy and safety of programmed death 1 (PD-1)/programmed death-ligand 1 (PD-L1) combined with cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) inhibitors for patients with advanced or metastatic non-small cell lung cancer (NSCLC).

METHODS

Authors conducted a comprehensive search of PubMed, Embase, Cochrane Library, Web of Science, Scopus, and Medline for randomized controlled trials comparing the prognosis and safety of PD-1/PD-L1 plus CTLA-4 inhibitors with other therapies for advanced or metastatic NSCLC. Hazard ratios (HRs) and 95% confidence intervals (CIs) were used as effect sizes. The primary outcomes of this study were overall survival (OS) and progression-free survival.

RESULTS

A total of 4943 patients diagnosed with stage III/IV advanced or metastatic NSCLC were included in the analysis of the 6 randomized controlled trials. The results showed that patients receiving dual immunotherapy with PD-1/PD-L1 plus CTLA-4 inhibitors had a longer survival time compared with the control group (HR = 0.88, P = 0.044). However, no statistically significant difference was observed in progression-free survival (HR = 0.95, P = 0.579). Subgroup analysis revealed better OS in the interventional group for patients aged >65 years (HR = 0.88, P = 0.076), smokers (HR = 0.81, P = 0.036), and those with a tumor mutational burden (TMB) ≥20 mut/Mb (HR = 0.66, P < 0.001). Conversely, the control group demonstrated superior OS in patients with TMB <20 mut/Mb (HR = 1.14, P = 0.048). In addition, the statistical results indicated a lower incidence rate of any-grade anemia in the dual immunotherapy group compared with the control group (RR = 0.32, P = 0.04).

CONCLUSIONS

This meta-analysis demonstrates the effectiveness and safety of dual immunotherapy with PD-1/PD-L1 plus CTLA-4 inhibitors for treating advanced or metastatic NSCLC. Its efficacy is influenced by certain clinical and pathological factors, such as age, smoking status, and TMB.

Additional impact of genetic ancestry over race/ethnicity to prevalence of KRAS mutations and allele-specific subtypes in non-small cell lung cancer

The KRAS mutation is the most common oncogenic driver in patients with non-small cell lung cancer (NSCLC). However, a detailed understanding of how self-reported race and/or ethnicity (SIRE), genetically inferred ancestry (GIA), and their interaction affect KRAS mutation is largely unknown. Here, we investigated the associations between SIRE, quantitative GIA, and KRAS mutation and its allele-specific subtypes in a multi-ethnic cohort of 3,918 patients from the Boston Lung Cancer Survival cohort and the Chinese OrigiMed cohort with an independent validation cohort of 1,450 patients with NSCLC. This comprehensive analysis included detailed covariates such as age at diagnosis, sex, clinical stage, cancer histology, and smoking status. We report that SIRE is significantly associated with KRAS mutations, modified by sex, with SIRE-Asian patients showing lower rates of KRAS mutation, transversion substitution, and the allele-specific subtype KRASG12C compared to SIRE-White patients after adjusting for potential confounders. Moreover, GIA was found to correlate with KRAS mutations, where patients with a higher proportion of European ancestry had an increased risk of KRAS mutations, especially more transition substitutions and KRASG12D. Notably, among SIRE-White patients, an increase in European ancestry was linked to a higher likelihood of KRAS mutations, whereas an increase in admixed American ancestry was associated with a reduced likelihood, suggesting that quantitative GIA offers additional information beyond SIRE. The association of SIRE, GIA, and their interplay with KRAS driver mutations in NSCLC highlights the importance of incorporating both into population-based cancer research, aiming to refine clinical decision-making processes and mitigate health disparities.

The crosstalk between immune cells and tumor pyroptosis: advancing cancer immunotherapy strategies

Pyroptosis is a cell death process characterized by cell swelling until membrane rupture and release of intracellular contents. As an effective tumor treatment strategy, inducing tumor cell pyroptosis has received widespread attention. In this process, the immune components within the tumor microenvironment play a key regulatory role. By regulating and altering the functions of immune cells such as cytotoxic T lymphocytes, natural killer cells, tumor-associated macrophages, and neutrophils, tumor cell pyroptosis can be induced. This article provides a comprehensive review of the molecular mechanisms of cell pyroptosis, the impact of the tumor immune microenvironment on tumor cell pyroptosis, and its mechanisms. It aims to gain an in-depth understanding of the communication between the tumor immune microenvironment and tumor cells, and to provide theoretical support for the development of new tumor immunotherapies.

The Macrophage migration inhibitory factor is a vital player in Pan-Cancer by functioning as a M0 Macrophage biomarker

BACKGROUND

The role of the macrophage migration inhibitory factor (MIF) has recently attracted considerable attention in cancer research; nonetheless, the insights provided by current investigations remain constrained. Our main objective was to investigate its role and the latent mechanisms within the pan-cancer realm.

METHODS

We used comprehensive pan-cancer bulk sequencing data and online network tools to investigate the association between MIF expression and patient prognosis, genomic instability, cancer cell stemness, DNA damage repair, and immune infiltration. Furthermore, we validated the relationship between MIF expression and M0 macrophages using single-cell datasets, the SpatialDB database, and fluorescence staining. Additionally, we assessed the therapeutic response using the ROC plotter tool.

RESULTS

We observed the upregulation of MIF expression across numerous cancer types. Notably, elevated MIF levels were associated with a decline in genomic stability. We found a significant correlation between increased MIF expression and increased expression of mismatch repair genes, stemness features, and homologous recombination genes across diverse malignancies. Subsequently, through an analysis using ESTIMATE and cytokine results, we revealed the involvement of MIF in immune suppression. Then, we validated MIF as a hallmark of the M0 macrophages involved in tumor immunity. Our study suggests an association with other immune-inhibitory cellular populations and restraint of CD8 + T cells. In addition, we conducted a comparative analysis of MIF expression before and after treatment in three distinct sets of therapy responders and non-responders. Intriguingly, we identified notable disparities in MIF expression patterns in bladder urothelial carcinoma and ovarian cancer following particular therapeutic interventions.

CONCLUSION

Comprehensive pan-cancer analysis revealed notable enrichment of MIF within M0 macrophages, exerting a profound influence on tumor-associated immunosuppression and the intricate machinery of DNA repair.

Artificial Intelligence in Oncology: Current Landscape, Challenges, and Future Directions

Artificial intelligence (AI) in oncology is advancing beyond algorithm development to integration into clinical practice. This review describes the current state of the field, with a specific focus on clinical integration. AI applications are structured according to cancer type and clinical domain, focusing on the four most common cancers and tasks of detection, diagnosis, and treatment. These applications encompass various data modalities, including imaging, genomics, and medical records. We conclude with a summary of existing challenges, evolving solutions, and potential future directions for the field.

SIGNIFICANCE

AI is increasingly being applied to all aspects of oncology, where several applications are maturing beyond research and development to direct clinical integration. This review summarizes the current state of the field through the lens of clinical translation along the clinical care continuum. Emerging areas are also highlighted, along with common challenges, evolving solutions, and potential future directions for the field.

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.

Mechanisms of resistance to targeted therapy and immunotherapy in non-small cell lung cancer: promising strategies to overcoming challenges

Resistance to targeted therapy and immunotherapy in non-small cell lung cancer (NSCLC) is a significant challenge in the treatment of this disease. The mechanisms of resistance are multifactorial and include molecular target alterations and activation of alternative pathways, tumor heterogeneity and tumor microenvironment change, immune evasion, and immunosuppression. Promising strategies for overcoming resistance include the development of combination therapies, understanding the resistance mechanisms to better use novel drug targets, the identification of biomarkers, the modulation of the tumor microenvironment and so on. Ongoing research into the mechanisms of resistance and the development of new therapeutic approaches hold great promise for improving outcomes for patients with NSCLC. Here, we summarize diverse mechanisms driving resistance to targeted therapy and immunotherapy in NSCLC and the latest potential and promising strategies to overcome the resistance to help patients who suffer from NSCLC.

Identification of germline population variants misclassified as cancer-associated somatic variants

Introduction

Databases used for clinical interpretation in oncology rely on genetic data derived primarily from patients of European ancestry, leading to biases in cancer genetics research and clinical practice. One practical issue that arises in this context is the potential misclassification of multi-ancestral population variants as tumor-associated because they are not represented in reference genomes against which tumor sequencing data is aligned.

Methods

To systematically find misclassified variants, we compared somatic variants in census genes from the Catalogue of Somatic Mutations in Cancer (COSMIC) V99 with multi-ancestral population variants from the Genome Aggregation Databases' Linkage Disequilibrium (GnomAD). By comparing genomic coordinates, reference, and alternate alleles, we could identify misclassified variants in genes associated with cancer.

Results

We found 192 of 208 genes in COSMIC's cancer-associated census genes (92.31%) to be associated with variant misclassifications. Among the 1,906,732 variants in COSMIC, 6,957 variants (0.36%) aligned with normal population variants in GnomAD, concerning for misclassification. The African / African American ancestral population included the greatest number of misclassified variants and also had the greatest number of unique misclassified variants.

Conclusion

The direct, systematic comparison of variants from COSMIC for co-occurrence in GnomAD supports a more accurate interpretation of tumor sequencing data and reduces bias related to genomic ancestry.

Genomic ancestry in kidney cancer: Correlations with clinical and molecular features

INTRODUCTION

Genetic ancestry (GA) refers to population hereditary patterns that contribute to phenotypic differences seen among race/ethnicity groups, and differences among GA groups may highlight unique biological determinants that add to our understanding of health care disparities.

METHODS

A retrospective review of patients with renal cell carcinoma (RCC) was performed and correlated GA with clinicopathologic, somatic, and germline molecular data. All patients underwent next-generation sequencing of normal and tumor DNA using Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets, and contribution of African (AFR), East Asian (EAS), European (EUR), Native American, and South Asian (SAS) ancestry was inferred through supervised ADMIXTURE. Molecular data was compared across GA groups by Fisher exact test and Kruskal-Wallis test.

RESULTS

In 953 patients with RCC, the GA distribution was: EUR (78%), AFR (4.9%), EAS (2.5%), SAS (2%), Native American (0.2%), and Admixed (12.2%). GA distribution varied by tumor histology and international metastatic RCC database consortium disease risk status (intermediate-poor: EUR 58%, AFR 88%, EAS 74%, and SAS 73%). Pathogenic/likely pathogenic germline variants in cancer-predisposition genes varied (16% EUR, 23% AFR, 8% EAS, and 0% SAS), and most occurred in CHEK2 in EUR (3.1%) and FH in AFR (15.4%). In patients with clear cell RCC, somatic alteration incidence varied with significant enrichment in BAP1 alterations (EUR 17%, AFR 50%, SAS 29%; p = .01). Comparing AFR and EUR groups within The Cancer Genome Atlas, significant differences were identified in angiogenesis and inflammatory pathways.

CONCLUSION

Differences in clinical and molecular data by GA highlight population-specific variations in patients with RCC. Exploration of both genetic and nongenetic variables remains critical to optimize efforts to overcome health-related disparities.

Detecting Somatic Mutations Without Matched Normal Samples Using Long Reads

DNA sequencing of tumours to identify somatic mutations has become a critical tool to guide the type of treatment given to cancer patients. The gold standard for mutation calling is comparing sequencing data from the tumour to a matched normal sample to avoid mis-classifying inherited SNPs as mutations. This procedure works extremely well, but in certain situations only a tumour sample is available. While approaches have been developed to find mutations without a matched normal, they have limited accuracy or require specific types of input data (e.g. ultra-deep sequencing). Here we explore the application of single molecule long read sequencing to calling somatic mutations without matched normal samples. We develop a simple theoretical framework to show how haplotype phasing is an important source of information for determining whether a variant is a somatic mutation. We then use simulations to assess the range of experimental parameters (tumour purity, sequencing depth) where this approach is effective. These ideas are developed into a prototype somatic mutation caller, smrest, and its use is demonstrated on two highly mutated cancer cell lines. Finally, we argue that this approach has potential to measure clinically important biomarkers that are based on the genome-wide distribution of mutations: tumour mutation burden and mutation signatures.

A comprehensive analysis of clinical and polygenic germline influences on somatic mutational burden

Tumor mutational burden (TMB), the total number of somatic mutations in the tumor, and copy number burden (CNB), the corresponding measure of aneuploidy, are established fundamental somatic features and emerging biomarkers for immunotherapy. However, the genetic and non-genetic influences on TMB/CNB and, critically, the manner by which they influence patient outcomes remain poorly understood. Here, we present a large germline-somatic study of TMB/CNB with >23,000 individuals across 17 cancer types, of which 12,000 also have extensive clinical, treatment, and overall survival (OS) measurements available. We report dozens of clinical associations with TMB/CNB, observing older age and male sex to have a strong effect on TMB and weaker impact on CNB. We additionally identified significant germline influences on TMB/CNB, including fine-scale European ancestry and germline polygenic risk scores (PRSs) for smoking, tanning, white blood cell counts, and educational attainment. We quantify the causal effect of exposures on somatic mutational processes using Mendelian randomization. Many of the identified features associated with TMB/CNB were additionally associated with OS for individuals treated at a single tertiary cancer center. For individuals receiving immunotherapy, we observed a complex relationship between PRSs for educational attainment, self-reported college attainment, TMB, and survival, suggesting that the influence of this biomarker may be substantially modified by socioeconomic status. While the accumulation of somatic alterations is a stochastic process, our work demonstrates that it can be shaped by host characteristics including germline genetics.

Comprehensive genomic profiling of penile squamous cell carcinoma and the impact of human papillomavirus status on immune-checkpoint inhibitor-related biomarkers

BACKGROUND

Advanced penile squamous cell carcinoma (pSCC) is a rare and aggressive malignancy with limited success of immune-checkpoint inhibitors (ICIs). Approximately half of pSCC cases are associated with human papillomavirus (HPV) infection.

METHODS

Evaluation was done retrospectively of the landscape of somatic alterations and ICI-related biomarkers in pSCC by using the Caris Life Sciences data set with the aim to establish signatures for HPV-dependent oncogenesis. The pSCC tumors were analyzed by using next-generation sequencing (NGS) of DNA and RNA. Programmed death ligand 1 (PD-L1) expression was evaluated by immunohistochemistry (IHC). Microsatellite instability (MSI) was tested by fragment analysis, IHC (SP142; ≥1%), and NGS. Tumor mutational burden (TMB)-high was defined as ≥10 mutations/Mb. HPV16/18 status was determined by using whole-exome sequencing (WES) when available. Significance was adjusted for multiple comparisons (q value < .05).

RESULTS

NGS of the overall cohort (N = 108) revealed TP53 (46%), CDKN2A (26%), and PIK3CA (25%) to be the most common mutations. Overall, 51% of tumors were PD-L1+, 10.7% had high TMB, and 1.1% had mismatch repair-deficient (dMMR)/MSI-high status. Twenty-nine patients had their HPV status made available by WES (HPV16/18+, n = 13; HPV16/18-, n = 16). KMT2C mutations (33% vs. 0%) and FGF3 amplifications (30.8% vs. 0%) were specific to HPV16/18+ tumors, whereas CDKN2A mutations (0% vs. 37.5%) were exclusive to HPV16/18- tumors. TMB-high was exclusively found in the HPV16/18+ group (30.8%). The two groups had comparable PD-L1 and dMMR/MSI-H status.

CONCLUSIONS

In a large and comprehensive NGS-based evaluation of somatic alterations in pSCC, HPV16/18+ versus HPV16/18- pSCCs were molecularly distinct tumors. Our finding that TMB-high is exclusive to HPV16/18+ tumors requires confirmation in larger data sets.

PLAIN LANGUAGE SUMMARY

Penile squamous cell carcinoma (pSCC) is a rare and aggressive malignancy in the advanced setting, with poor prognosis and little success with immune-checkpoint inhibitors (ICIs) in an unselected patient approach. Human papillomavirus (HPV) infection is a known risk factor for pSCC; its impact on genomic tumor profiling is less defined. Using next-generation sequencing, we explored the genetic landscape and ICI-related biomarkers of pSCC and HPV-driven oncogenic molecular signatures. Our results indicate that HPV-positive and HPV-negative pSCCs are molecularly distinct tumors. Increased tumor mutational burden is associated with HPV-positive tumors, and could serve as a biomarker for predicting therapeutic response to ICI-based therapies. Our results support the growing literature indicating that HPV status in pSCC can be used to guide patient stratification in ICI-based clinical trials.

Challenges and Future Directions in the Management of Tumor Mutational Burden-High (TMB-H) Advanced Solid Malignancies

A standardized assessment of Tumor Mutational Burden (TMB) poses challenges across diverse tumor histologies, treatment modalities, and testing platforms, requiring careful consideration to ensure consistency and reproducibility. Despite clinical trials demonstrating favorable responses to immune checkpoint inhibitors (ICIs), not all patients with elevated TMB exhibit benefits, and certain tumors with a normal TMB may respond to ICIs. Therefore, a comprehensive understanding of the intricate interplay between TMB and the tumor microenvironment, as well as genomic features, is crucial to refine its predictive value. Bioinformatics advancements hold potential to improve the precision and cost-effectiveness of TMB assessments, addressing existing challenges. Similarly, integrating TMB with other biomarkers and employing comprehensive, multiomics approaches could further enhance its predictive value. Ongoing collaborative endeavors in research, standardization, and clinical validation are pivotal in harnessing the full potential of TMB as a biomarker in the clinic settings.

Roles of tissue-resident immune cells in immunotherapy of non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is the most common and lethal type of lung cancer, with limited treatment options and poor prognosis. Immunotherapy offers hope for improving the survival and quality of life of NSCLC patients, but its efficacy depends on the tumor immune microenvironment (TME). Tissue-resident immune cells are a subset of immune cells that reside in various tissues and organs, and play an important role in fighting tumors. In NSCLC, tissue-resident immune cells are heterogeneous in their distribution, phenotype, and function, and can either promote or inhibit tumor progression and response to immunotherapy. In this review, we summarize the current understanding on the characteristics, interactions, and roles of tissue-resident immune cells in NSCLC. We also discuss the potential applications of tissue-resident immune cells in NSCLC immunotherapy, including immune checkpoint inhibitors (ICIs), other immunomodulatory agents, and personalized cell-based therapies. We highlight the challenges and opportunities for developing targeted therapies for tissue-resident immune cells and optimizing existing immunotherapeutic approaches for NSCLC patients. We propose that tissue-resident immune cells are a key determinant of NSCLC outcome and immunotherapy response, and warrant further investigation in future research.

Tumor Mutational Burden Testing in Solid Tumors

A 58-year-old man with diabetes, chronic kidney disease, and JAK2-positive myeloproliferative neoplasm is referred for newly diagnosed oligometastatic prostate cancer with substantial urinary symptoms. What would you do next?

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.

Tumor sequencing of African ancestry reveals differences in clinically relevant alterations across common cancers

Cancer genomes from patients with African (AFR) ancestry have been poorly studied in clinical research. We leverage two large genomic cohorts to investigate the relationship between genomic alterations and AFR ancestry in six common cancers. Cross-cancer type associations, such as an enrichment of MYC amplification with AFR ancestry in lung, breast, and prostate cancers, and depletion of BRAF alterations are observed in colorectal and pancreatic cancers. There are differences in actionable alterations, such as depletion of KRAS G12C and EGFR L858R, and enrichment of ROS1 fusion with AFR ancestry in lung cancers. Interestingly, in lung cancer, KRAS mutations are less common in both smokers and non-smokers with AFR ancestry, whereas the association of TP53 mutations with AFR ancestry is only seen in smokers, suggesting an ancestry-environment interaction that modifies driver rates. Our study highlights the need to increase representation of patients with AFR ancestry in drug development and biomarker discovery.

Molecular Characterization of Endometrial Carcinomas in Black and White Patients Reveals Disparate Drivers with Therapeutic Implications

Although the incidence of endometrial carcinoma (EC) is similar in Black and White women, racial disparities are stark, with the highest mortality rates observed among Black patients. Here, analysis of 1,882 prospectively sequenced ECs using a clinical FDA-authorized tumor-normal panel revealed a significantly higher prevalence of high-risk histologic and molecular EC subtypes in self-identified Black (n = 259) compared with White (n = 1,623) patients. Clinically actionable alterations, including high tumor mutational burden/microsatellite instability, which confer benefit from immunotherapy, were less frequent in ECs from Black than from White patients. Ultramutated POLE molecular subtype ECs associated with favorable outcomes were rare in Black patients. Results were confirmed by genetic ancestry analysis. CCNE1 gene amplification, which is associated with aggressive clinical behavior, was more prevalent in carcinosarcomas occurring in Black than in White patients. ECs from Black and White patients display important differences in their histologic types, molecular subtypes, driver genetic alterations, and therapeutic targets.

SIGNIFICANCE

Our comprehensive analysis of prospectively clinically sequenced ECs revealed significant differences in their histologic and molecular composition and in the presence of therapeutic targets in Black versus White patients. These findings emphasize the importance of incorporating diverse populations into molecular studies and clinical trials to address EC disparities. This article is featured in Selected Articles from This Issue, p. 2293.

Clinicopathological characteristics correlated with programmed cell death-ligand 1 expression in advanced lung adenocarcinoma

Background

Recent studies have shown that immune checkpoint inhibitors (ICIs) targeting programmed cell death-ligand 1 (PD-L1) have potential benefits in patients with non-small cell lung cancer (NSCLC) subgroups, while the clinicopathological characteristics associated with PD-L1 expression have not been well established. The purpose of this study was to detect the expression level of PD-L1 in tumor tissues of patients with advanced lung adenocarcinoma (ADC) and analyze its possible relationship with clinicopathological characteristics, so as to identify the predictors of PD-L1 expression.

Methods

This retrospective study was conducted by analyzing the clinicopathological and imaging characteristics of hospitalized advanced lung ADC patients with PD-L1 available data and admitted to the respiratory department of our hospital. The expression level of PD-L1 in fresh-frozen tumor tissue samples of 136 advanced ADC patients was analyzed by immunohistochemistry. The patients were divided into positive and negative groups based on a cut-off of 1% PD-L1 expression level. Subsequently, the significant correlation between PD-L1 levels and clinicopathological features were evaluated. The predictive performance of clinicopathological characteristics on PD-L1 expression was evaluated and the optimal cut-off values were identified by plotting the receiver operating characteristic (ROC) curve.

Results

The expression level of PD-L1 was related to sex, clinical stage, serum carcinoembryonic antigen (CEA), neuron specific enolase (NSE), white blood cell (WBC), and tumor (T) and metastasis (M) stage. Multivariate logistic regression analysis showed the CEA, NSE, T stage, and WBC were independent predictors of PD-L1 positive expression in lung ADC patients. The ROC curve suggested the model combining CEA with NSE [area under the curve (AUC) =0.815] could better predict the expression levels of PD-L1. The optimal cut-off values for identifying advanced lung ADC patients with PD-L1 positive were CEA ≤13.38 ng/mL and NSE ≤42.35 ng/mL, with sensitivity and specificity of 85.4% and 55.6%, and 92.7% and 32.1%, respectively.

Conclusions

Some commonly used clinicopathological features are related to the histological expression of PD-L1. The serum CEA, NSE, T stage, and WBC values can be used as indicators to predict the expression level of PD-L1 in advanced lung ADC, and are used as predictors to evaluate the efficacy of ICIs before treatment.

Research advances in mechanism of antiangiogenic therapy combined with immune checkpoint inhibitors for treatment of non-small cell lung cancer

Immunotherapy has changed the treatment strategy of non-small cell lung cancer (NSCLC) in recent years, among which anti-PD-1/PD-L1 antibodies are the most used. However, the majority of patients with NSCLC do not derive benefit from immune checkpoint inhibitors (ICIs). Vascular abnormalities are a hallmark of most solid tumors and facilitate immune evasion. Thus, combining antiangiogenic therapies might increase the effectiveness of anti-PD-1/PD-L1 antibodies. In this paper, the mechanisms of anti-angiogenic agents combined with anti-PD-1/PD-L1 antibodies are illustrated, moreover, relevant clinical studies and predictive immunotherapeutic biomarkers are summarized and analyzed, in order to provide more treatment options for NSCLC patients.

Progresses in biomarkers for cancer immunotherapy

Currently, checkpoint inhibitor-based immunotherapy has emerged as prevailing treatment modality for diverse cancers. However, immunotherapy as a first-line therapy has not consistently yielded durable responses. Moreover, the risk of immune-related adverse events increases with combination regimens. Thus, the development of predictive biomarkers is needed to optimize individuals benefit, minimize risk of toxicities, and guide combination approaches. The greatest focus has been on tumor programmed cell death-ligand 1 (PD-L1), microsatellite instability (MSI), and tumor mutational burden (TMB). However, there remains a subject of debate due to thresholds variability and significant heterogeneity. Major unmet challenges in immunotherapy are the discovery and validation of predictive biomarkers. Here, we show the status of tumor PD-L1, MSI, TMB, and emerging data on novel biomarker strategies with oncogenic signaling and epigenetic regulation. Considering the exploration of peripheral and intestinal immunity has served as noninvasive alternative in predicting immunotherapy, this review also summarizes current data in systemic immunity, encompassing solute PD-L1 and TMB, circulating tumor DNA and infiltrating lymphocytes, routine emerging inflammatory markers and cytokines, as well as gut microbiota. This review provides up-to-date information on the evolving field of currently available biomarkers in predicting immunotherapy. Future exploration of novel biomarkers is warranted.

Stromal heterogeneity may explain increased incidence of metaplastic breast cancer in women of African descent

The biologic basis of genetic ancestry-dependent variability in disease incidence and outcome is just beginning to be explored. We recently reported enrichment of a population of ZEB1-expressing cells located adjacent to ductal epithelial cells in normal breasts of women of African ancestry compared to those of European ancestry. In this study, we demonstrate that these cells have properties of fibroadipogenic/mesenchymal stromal cells that express PROCR and PDGFRα and transdifferentiate into adipogenic and osteogenic lineages. PROCR + /ZEB1 + /PDGFRα+ (PZP) cells are enriched in normal breast tissues of women of African compared to European ancestry. PZP: epithelial cell communication results in luminal epithelial cells acquiring basal cell characteristics and IL-6-dependent increase in STAT3 phosphorylation. Furthermore, level of phospho-STAT3 is higher in normal and cancerous breast tissues of women of African ancestry. PZP cells transformed with HRasG12V ± SV40-T/t antigens generate metaplastic carcinoma suggesting that these cells are one of the cells-of-origin of metaplastic breast cancers.

Utility of Tumor Mutational Burden as a Biomarker for Response to Immune Checkpoint Inhibition in the VA Population

PURPOSE

Immune checkpoint inhibitors (ICIs) are used for an increasing number of indications across various tumor types, as well as several tumor-agnostic indications in patients with advanced cancer. Although many patients benefit from ICI therapy, others do not, highlighting a need for better predictive biomarkers. Tumor mutational burden (TMB) reflects the global number of mutations within a tumor and has been widely explored as a predictive biomarker of ICI response. The current tumor type-agnostic US Food and Drug Administration approval of pembrolizumab for metastatic solid tumors defines high TMB (TMB-H) as ≥10 mut/Mb as measured by FoundationOne CDx. This fixed cutoff may not be the ideal value across all solid tumors.

METHODS

We performed a retrospective analysis of the association of survival outcomes with TMB in patients treated with ICI for five major cancer types, using real-world data from the VA. Survival was measured from initiation of ICI, and Kaplan-Meier survival curves were compared by log-rank test.

RESULTS

Overall survival (OS) was significantly longer for patients with TMB-H versus TMB low tumors in non-small-cell lung cancer (NSCLC; n = 1,593), head and neck (H&N) cancer (n = 222), and urothelial cancer (n = 332). OS was not significantly different based on TMB status in melanoma (n = 207) or esophageal/gastric cancer (n = 248).

CONCLUSION

Consistent with previous studies, a predictive value of TMB ≥10 mut/Mb for ICI response was found in NSCLC and H&N, but not in esophageal/gastric cancer. Although inconclusive in the literature, significant association was found in urothelial cancer. The predictive value of TMB in melanoma was inconclusive. Our analysis does not support the use of a fixed threshold for TMB as a standalone predictive biomarker for ICI across all solid tumors.

Germline mechanisms of immunotherapy toxicities in the era of genome-wide association studies

Cancer immunotherapy has revolutionized the treatment of advanced cancers and is quickly becoming an option for early-stage disease. By reactivating the host immune system, immunotherapy harnesses patients' innate defenses to eradicate the tumor. By putatively similar mechanisms, immunotherapy can also substantially increase the risk of toxicities or immune-related adverse events (irAEs). Severe irAEs can lead to hospitalization, treatment discontinuation, lifelong immune complications, or even death. Many irAEs present with similar symptoms to heritable autoimmune diseases, suggesting that germline genetics may contribute to their onset. Recently, genome-wide association studies (GWAS) of irAEs have identified common germline associations and putative mechanisms, lending support to this hypothesis. A wide range of well-established GWAS methods can potentially be harnessed to understand the etiology of irAEs specifically and immunotherapy outcomes broadly. This review summarizes current findings regarding germline effects on immunotherapy outcomes and discusses opportunities and challenges for leveraging germline genetics to understand, predict, and treat irAEs.

Understanding the Impact of Population and Cancer Type on Tumor Mutation Burden Scores: A Comprehensive Whole-Exome Study in Cancer Patients From India

PURPOSE

The purpose of this study was to understand the impact of population diversity and geographic variation on tumor mutation burden (TMB) scores across cancers and its implication on stratification of patients for immune checkpoint inhibitor (ICI) therapy.

MATERIALS AND METHODS

This retrospective study used whole-exome sequencing (WES) to profile 1,233 Indian patients with cancer across 30 different cancer types and to estimate their TMB scores. A WES-based pipeline was adopted, along with an indigenously developed strategy for arriving at true somatic mutations. A robust unsupervised machine learning approach was used to understand the distribution of TMB scores across different populations and within the population.

RESULTS

The results of the study showed a biphasic distribution of TMB scores in most cancers, with different threshold scores across cancer types. Patients with cancer in India had higher TMB scores compared with the Caucasian patients. We also observed that the TMB score value at 90th percentile (predicting high efficacy to ICI) was high in four different cancer types (sarcoma, ovary, head and neck, and breast) in the Indian cohort as compared with The Cancer Genome Atlas or public cohort. However, in lung and colorectal cancers, the TMB score distribution was similar between the two population cohorts.

CONCLUSION

The findings of this study indicate that it is crucial to benchmark both cancer-specific and population-specific TMB distributions to establish a TMB threshold for each cancer in various populations. Additional prospective studies on much larger population across different cancers are warranted to validate this observation to become the standard of care.

Tackling the lack of diversity in cancer research

Despite the clear benefit of studying biological samples from diverse genetic backgrounds and geographical locations, our current knowledge of disease is mostly derived from the study of European-descent individuals. In the cancer field, this is reflected in the poor representation of African and Amerindian/Latino samples in most large public data repositories. This lack of diversity is due to several reasons, but here we focus on (1) the lack of support for studies on non-European populations that are performed in low- and middle-income countries (LMICs), and (2) unequal partnerships between scientists in LMICs and those in high-income countries. We argue that expanding access to research funding, increasing the participation of underrepresented scientists in editorial boards and international conferences, facilitating the publication of studies conducted in these countries, and properly acknowledging LMIC researchers' contributions in publications and grant applications will promote equity for scientists working in LMICs. We envisage that this will translate to more impactful research in these countries, which will include more samples from diverse populations. For the cancer field, this will broaden our understanding of pathomechanisms and may help to improve the treatment of patients from all backgrounds.

The prognostic value of TMB in early-stage non-small cell lung cancer: a systematic review and meta-analysis

Background

Tumor mutation burden (TMB) has been validated as a predictive biomarker for immunotherapy response and survival in numerous cancer types. Limited data is available on the inherent prognostic role of TMB in early-stage tumors.

Objective

To evaluate the prognostic role of TMB in early-stage, resected non-small cell lung cancer (NSCLC).

Design

Systematic review and meta-analysis of pertinent prospective and retrospective studies.

Data sources and methods

Publication search was performed in PubMed, Embase, Cochrane Library, and Web of Science databases. Based on the level of heterogeneity, a random- or fixed-effects model was used to calculate pooled effects of hazard ratio (HR) for overall survival (OS) and disease-free survival (DFS). The source of heterogeneity was investigated using sensitivity analysis, subgroup analysis, and publication bias assessment.

Results

Ten studies comprising 2520 patients were included in this analysis. There was no statistically significant difference in OS (HR, 1.18, 95% CI, 0.70, 1.33; p 0.53, I2 = 80%; phet < 0.0001) and DFS (HR, 1.18, 95% CI, 0.91, 1.52; p = 0.53, I2 = 75%; phet = 0.0001) between the high-TMB and low-TMB group. Subgroup analyses indicated that East Asian ethnicity, and TMB detected using whole exome sequencing, and studies with <100 patients had poor DFS in the high-TMB group.

Conclusion

The inherent prognostic role of TMB is limited in early-stage NSCLC. Ethnic differences in mutation burden must be considered while designing future trials on neoadjuvant immunotherapy. Further research in the harmonization and standardization of panel-based TMB is essential for its widespread clinical utility.Registration: CRD42023392846.

Analytic validation of NeXT Dx™, a comprehensive genomic profiling assay

We describe the analytic validation of NeXT Dx, a comprehensive genomic profiling assay to aid therapy and clinical trial selection for patients diagnosed with solid tumor cancers. Proprietary methods were utilized to perform whole exome and whole transcriptome sequencing for detection of single nucleotide variants (SNVs), insertions/deletions (indels), copy number alterations (CNAs), and gene fusions, and determination of tumor mutation burden and microsatellite instability. Variant calling is enhanced by sequencing a patient-specific normal sample from, for example, a blood specimen. This provides highly accurate somatic variant calls as well as the incidental reporting of pathogenic and likely pathogenic germline alterations. Fusion detection via RNA sequencing provides more extensive and accurate fusion calling compared to DNA-based tests. NeXT Dx features the proprietary Accuracy and Content Enhanced technology, developed to optimize sequencing and provide more uniform coverage across the exome. The exome was validated at a median sequencing depth of >500x. While variants from 401 cancer-associated genes are currently reported from the assay, the exome/transcriptome assay is broadly validated to enable reporting of additional variants as they become clinically relevant. NeXT Dx demonstrated analytic sensitivities as follows: SNVs (99.4%), indels (98.2%), CNAs (98.0%), and fusions (95.8%). The overall analytic specificity was >99.0%.

Immune checkpoint therapy for solid tumours: clinical dilemmas and future trends

Immune-checkpoint inhibitors (ICBs), in addition to targeting CTLA-4, PD-1, and PD-L1, novel targeting LAG-3 drugs have also been approved in clinical application. With the widespread use of the drug, we must deeply analyze the dilemma of the agents and seek a breakthrough in the treatment prospect. Over the past decades, these agents have demonstrated dramatic efficacy, especially in patients with melanoma and non-small cell lung cancer (NSCLC). Nonetheless, in the field of a broad concept of solid tumours, non-specific indications, inseparable immune response and side effects, unconfirmed progressive disease, and complex regulatory networks of immune resistance are four barriers that limit its widespread application. Fortunately, the successful clinical trials of novel ICB agents and combination therapies, the advent of the era of oncolytic virus gene editing, and the breakthrough of the technical barriers of mRNA vaccines and nano-delivery systems have made remarkable breakthroughs currently. In this review, we enumerate the mechanisms of each immune checkpoint targets, associations between ICB with tumour mutation burden, key immune regulatory or resistance signalling pathways, the specific clinical evidence of the efficacy of classical targets and new targets among different tumour types and put forward dialectical thoughts on drug safety. Finally, we discuss the importance of accurate triage of ICB based on recent advances in predictive biomarkers and diagnostic testing techniques.

Tumor Mutational Burden in Breast Cancer: Current Evidence, Challenges, and Opportunities

Tumor mutational burden (TMB) correlates with tumor neoantigen burden, T cell infiltration, and response to immune checkpoint inhibitors in many solid tumor types. Based on data from the phase II KEYNOTE-158 study, the anti-PD-1 antibody pembrolizumab was granted approval for treating patients with advanced solid tumors and TMB ≥ 10 mutations per megabase. However, this trial did not include any patients with metastatic breast cancer; thus, several questions remain unanswered about the true role of TMB as a predictive biomarker of benefit to immune checkpoint inhibitor therapy in breast cancer. In this review, we will discuss the challenges and opportunities in establishing TMB as a predictive biomarker of benefit to immunotherapy in metastatic breast cancer.

Multimodal molecular landscape of response to Y90-resin microsphere radioembolization followed by nivolumab for advanced hepatocellular carcinoma

BACKGROUND

Combination therapy with radioembolization (yttrium-90)-resin microspheres) followed by nivolumab has shown a promising response rate of 30.6% in a Phase II trial (CA209-678) for advanced hepatocellular carcinoma (HCC); however, the response mechanisms and relevant biomarkers remain unknown.

METHODS

By collecting both pretreatment and on-treatment samples, we performed multimodal profiling of tissue and blood samples and investigated molecular changes associated with favorable responses in 33 patients from the trial.

RESULTS

We found that higher tumor mutation burden, NCOR1 mutations and higher expression of interferon gamma pathways occurred more frequently in responders. Meanwhile, non-responders tended to be enriched for a novel Asian-specific transcriptomic subtype (Kaya_P2) with a high frequency of chromosome 16 deletions and upregulated cell cycle pathways. Strikingly, unlike other cancer types, we did not observe any association between T-cell populations and treatment response, but tumors from responders had a higher proportion of CXCL9+/CXCR3+ macrophages. Moreover, biomarkers discovered in previous immunotherapy trials were not predictive in the current cohort, suggesting a distinctive molecular landscape associated with differential responses to the combination therapy.

CONCLUSIONS

This study unraveled extensive molecular changes underlying distinctive responses to the novel treatment and pinpointed new directions for harnessing combination therapy in patients with advanced HCC.

Lung cancer in never smokers (LCINS): development of a UK national research strategy

INTRODUCTION

Lung cancer in never smokers (LCINS) accounts for 15% of lung cancers diagnosed in the UK, making it the 8th most common cancer. There are few robust studies specific to the LCINS population making data surrounding the incidence and mortality of LCINS incomplete, leaving many gaps in our understanding of the needs of this population.

METHODS

To address a lack of research in this important area, the UK National Cancer Research Institute Lung Study Group (NCRI-LSG) undertook a national survey and hosted a research strategy day to define key research priorities. A wide cross section of stakeholders, including patient advocates, the charitable sector, basic and translational researchers, and multi-disciplinary healthcare professionals contributed highlighting their research priorities.

RESULTS

One-hundred twenty-seven surveys were completed (52 by patients/patient advocates) prior to the strategy day. These identified themes for expert review presentations and subsequent workshop discussions at the national research strategy day, which registered 190 attendees (50 patients/patient advocates). The four key themes that emerged to form the basis of a research strategy for LCINS are (1) Raising awareness, (2) Risk assessment and early detection, (3) Disease biology, (4) Living with and beyond.

CONCLUSION

This paper summarises current evidence and important gaps in our knowledge related to LCINS. We present recommendations for a national research strategy aimed at improving outcomes for patients.

Validation of Immunotherapy Response Score as Predictive of Pan-solid Tumor Anti-PD-1/PD-L1 Benefit

Immunotherapy response score (IRS) integrates tumor mutation burden (TMB) and quantitative expression biomarkers to predict anti-PD-1/PD-L1 [PD-(L)1] monotherapy benefit. Here, we evaluated IRS in additional cohorts. Patients from an observational trial (NCT03061305) treated with anti-PD-(L)1 monotherapy were included and assigned to IRS-High (-H) versus -Low (-L) groups. Associations with real-world progression-free survival (rwPFS) and overall survival (OS) were determined by Cox proportional hazards (CPH) modeling. Those with available PD-L1 IHC treated with anti-PD-(L)1 with or without chemotherapy were separately assessed. Patients treated with PD-(L)1 and/or chemotherapy (five relevant tumor types) were assigned to three IRS groups [IRS-L divided into IRS-Ultra-Low (-UL) and Intermediate-Low (-IL), and similarly assessed]. In the 352 patient anti-PD-(L)1 monotherapy validation cohort (31 tumor types), IRS-H versus IRS-L patients had significantly longer rwPFS and OS. IRS significantly improved CPH associations with rwPFS and OS beyond microsatellite instability (MSI)/TMB alone. In a 189 patient (10 tumor types) PD-L1 IHC comparison cohort, IRS, but not PD-L1 IHC nor TMB, was significantly associated with anti-PD-L1 rwPFS. In a 1,103-patient cohort (from five relevant tumor types), rwPFS did not significantly differ in IRS-UL patients treated with chemotherapy versus chemotherapy plus anti-PD-(L)1, nor in IRS-H patients treated with anti-PD-(L)1 versus anti-PD-(L)1 + chemotherapy. IRS associations were consistent across subgroups, including both Europeans and non-Europeans. These results confirm the utility of IRS utility for predicting pan-solid tumor PD-(L)1 monotherapy benefit beyond available biomarkers and demonstrate utility for informing on anti-PD-(L)1 and/or chemotherapy treatment.

Significance

This study confirms the utility of the integrative IRS biomarker for predicting anti-PD-L1/PD-1 benefit. IRS significantly improved upon currently available biomarkers, including PD-L1 IHC, TMB, and MSI status. Additional utility for informing on chemotherapy, anti-PD-L1/PD-1, and anti-PD-L1/PD-1 plus chemotherapy treatments decisions is shown.

Cutaneous immune-related adverse events to immune checkpoint inhibitors: from underlying immunological mechanisms to multi-omics prediction

The development of immune checkpoint inhibitors (ICIs) has dramatically altered the landscape of therapy for multiple malignancies, including urothelial carcinoma, non-small cell lung cancer, melanoma and gastric cancer. As part of their anti-tumor properties, ICIs can enhance susceptibility to inflammatory side effects known as immune-related adverse events (irAEs), in which the skin is one of the most commonly and rapidly affected organs. Although numerous questions still remain unanswered, multi-omics technologies have shed light into immunological mechanisms, as well as the correlation between ICI-induced activation of immune systems and the incidence of cirAE (cutaneous irAEs). Therefore, we reviewed integrated biological layers of omics studies combined with clinical data for the prediction biomarkers of cirAEs based on skin pathogenesis. Here, we provide an overview of a spectrum of dermatological irAEs, discuss the pathogenesis of this "off-tumor toxicity" during ICI treatment, and summarize recently investigated biomarkers that may have predictive value for cirAEs via multi-omics approach. Finally, we demonstrate the prognostic significance of cirAEs for immune checkpoint blockades.

Understanding inequities in precision oncology diagnostics

Advances in molecular diagnostics have enabled the identification of targetable driver pathogenic variants, forming the basis of precision oncology care. However, the adoption of new technologies, such as next-generation sequencing (NGS) panels, can exacerbate healthcare disparities. Here, we summarize data on use patterns of advanced biomarker testing, highlight the disparities in both accessing NGS testing and using this data to match patients to appropriate personalized therapies and propose multidisciplinary strategies to address inequities looking forward.

First-line therapy for adults with advanced renal cell carcinoma: a systematic review and network meta-analysis

BACKGROUND

Since the approval of tyrosine kinase inhibitors, angiogenesis inhibitors and immune checkpoint inhibitors, the treatment landscape for advanced renal cell carcinoma (RCC) has changed fundamentally. Today, combined therapies from different drug categories have a firm place in a complex first-line therapy. Due to the large number of drugs available, it is necessary to identify the most effective therapies, whilst considering their side effects and impact on quality of life (QoL).

OBJECTIVES

To evaluate and compare the benefits and harms of first-line therapies for adults with advanced RCC, and to produce a clinically relevant ranking of therapies. Secondary objectives were to maintain the currency of the evidence by conducting continuous update searches, using a living systematic review approach, and to incorporate data from clinical study reports (CSRs).

SEARCH METHODS

We searched CENTRAL, MEDLINE, Embase, conference proceedings and relevant trial registries up until 9 February 2022. We searched several data platforms to identify CSRs.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) evaluating at least one targeted therapy or immunotherapy for first-line treatment of adults with advanced RCC. We excluded trials evaluating only interleukin-2 versus interferon-alpha as well as trials with an adjuvant treatment setting. We also excluded trials with adults who received prior systemic anticancer therapy if more than 10% of participants were previously treated, or if data for untreated participants were not separately extractable.

DATA COLLECTION AND ANALYSIS

All necessary review steps (i.e. screening and study selection, data extraction, risk of bias and certainty assessments) were conducted independently by at least two review authors. Our outcomes were overall survival (OS), QoL, serious adverse events (SAEs), progression-free survival (PFS), adverse events (AEs), the number of participants who discontinued study treatment due to an AE, and the time to initiation of first subsequent therapy. Where possible, analyses were conducted for the different risk groups (favourable, intermediate, poor) according to the International Metastatic Renal-Cell Carcinoma Database Consortium Score (IMDC) or the Memorial Sloan Kettering Cancer Center (MSKCC) criteria. Our main comparator was sunitinib (SUN). A hazard ratio (HR) or risk ratio (RR) lower than 1.0 is in favour of the experimental arm.

MAIN RESULTS

We included 36 RCTs and 15,177 participants (11,061 males and 4116 females). Risk of bias was predominantly judged as being 'high' or 'some concerns' across most trials and outcomes. This was mainly due to a lack of information about the randomisation process, the blinding of outcome assessors, and methods for outcome measurements and analyses. Additionally, study protocols and statistical analysis plans were rarely available. Here we present the results for our primary outcomes OS, QoL, and SAEs, and for all risk groups combined for contemporary treatments: pembrolizumab + axitinib (PEM+AXI), avelumab + axitinib (AVE+AXI), nivolumab + cabozantinib (NIV+CAB), lenvatinib + pembrolizumab (LEN+PEM), nivolumab + ipilimumab (NIV+IPI), CAB, and pazopanib (PAZ). Results per risk group and results for our secondary outcomes are reported in the summary of findings tables and in the full text of this review. The evidence on other treatments and comparisons can also be found in the full text. Overall survival (OS) Across risk groups, PEM+AXI (HR 0.73, 95% confidence interval (CI) 0.50 to 1.07, moderate certainty) and NIV+IPI (HR 0.69, 95% CI 0.69 to 1.00, moderate certainty) probably improve OS, compared to SUN, respectively. LEN+PEM may improve OS (HR 0.66, 95% CI 0.42 to 1.03, low certainty), compared to SUN. There is probably little or no difference in OS between PAZ and SUN (HR 0.91, 95% CI 0.64 to 1.32, moderate certainty), and we are uncertain whether CAB improves OS when compared to SUN (HR 0.84, 95% CI 0.43 to 1.64, very low certainty). The median survival is 28 months when treated with SUN. Survival may improve to 43 months with LEN+PEM, and probably improves to: 41 months with NIV+IPI, 39 months with PEM+AXI, and 31 months with PAZ. We are uncertain whether survival improves to 34 months with CAB. Comparison data were not available for AVE+AXI and NIV+CAB. Quality of life (QoL) One RCT measured QoL using FACIT-F (score range 0 to 52; higher scores mean better QoL) and reported that the mean post-score was 9.00 points higher (9.86 lower to 27.86 higher, very low certainty) with PAZ than with SUN. Comparison data were not available for PEM+AXI, AVE+AXI, NIV+CAB, LEN+PEM, NIV+IPI, and CAB. Serious adverse events (SAEs) Across risk groups, PEM+AXI probably increases slightly the risk for SAEs (RR 1.29, 95% CI 0.90 to 1.85, moderate certainty) compared to SUN. LEN+PEM (RR 1.52, 95% CI 1.06 to 2.19, moderate certainty) and NIV+IPI (RR 1.40, 95% CI 1.00 to 1.97, moderate certainty) probably increase the risk for SAEs, compared to SUN, respectively. There is probably little or no difference in the risk for SAEs between PAZ and SUN (RR 0.99, 95% CI 0.75 to 1.31, moderate certainty). We are uncertain whether CAB reduces or increases the risk for SAEs (RR 0.92, 95% CI 0.60 to 1.43, very low certainty) when compared to SUN. People have a mean risk of 40% for experiencing SAEs when treated with SUN. The risk increases probably to: 61% with LEN+PEM, 57% with NIV+IPI, and 52% with PEM+AXI. It probably remains at 40% with PAZ. We are uncertain whether the risk reduces to 37% with CAB. Comparison data were not available for AVE+AXI and NIV+CAB.

AUTHORS' CONCLUSIONS

Findings concerning the main treatments of interest comes from direct evidence of one trial only, thus results should be interpreted with caution. More trials are needed where these interventions and combinations are compared head-to-head, rather than just to SUN. Moreover, assessing the effect of immunotherapies and targeted therapies on different subgroups is essential and studies should focus on assessing and reporting relevant subgroup data. The evidence in this review mostly applies to advanced clear cell RCC.