Racial disparities in patient survival and tumor mutation burden, and the association between tumor mutation burden and cancer incidence rate

The prognosis and treatment of newly diagnosed bone metastasis of head and neck squamous cell cancer: an analysis of racial disparity

OBJECTIVE

There is a lack of research investigating racial disparity in newly diagnosed head and neck squamous cell carcinoma with isolated bone metastases (HNSCC-BM). This study aims to investigate the clinical characteristics and prognostic factors in HNSCC-BM patients from different racial backgrounds to aid clinical decision making and management.

METHODS

We retrieved data from the Surveillance, Epidemiology, and End Results (SEER) database for 345 cases of HNSCC-BM that were diagnosed between 2010 and 2017. Survival was compared using univariate and multivariate Cox proportional hazards models, Kaplan-Meier analysis, and log-rank tests. We also used propensity score matching to adjust for confounders.

RESULTS

In white patients, those who were over 40 years of age had a significantly shorter survival (HR, 4.49; 95% CI 1.03-19.56; P < 0.05). Female black patients were found to survive longer compared to male patients (HR, 0.34; 95% CI 0.15-0.76; P < 0.01). Single (never married) Asians had shorter survival than married Asians (HR, 4.68; 95% CI 1.34-16.41; P < 0.05). In all three racial groups, patients who received radiotherapy in addition to chemotherapy did not survive longer than those receiving chemotherapy (P > 0.05). In Asian patients, those who underwent surgery at the primary site combined with chemoradiotherapy had significantly better survival outcomes than those who received chemoradiotherapy (HR: 0.10, 95% CI 0.01-0.88; P = 0.01).

CONCLUSION

Prognostic factors differ between HNSCC-BM patients from different racial backgrounds.

K-nearest-neighbor algorithm to predict the survival time and classification of various stages of oral cancer: a machine learning approach

Background:For years now, cancer treatments have entailed tried-and-true methods. Yet, oncologists and clinicians recommend a series of surgeries, chemotherapy, and radiation therapy. Yet, even amidst these treatments, the number of deaths due to cancer increases at an alarming rate. The prognosis of cancer patients is influenced by mutations, age, and various cancer stages. However, the association between these variables is unclear. Methods: The present work adopts a machine learning technique-k-nearest neighbor; for both regression and classification tasks, regression for predicting the survival time of oral cancer patients, and classification for classifying the patients into one of the predefined oral cancer stages. Two cross-validation approaches-hold-out and k-fold methods-have been used to examine the prediction results. Results: The experimental results show that the k-fold method performs better than the hold-out method, providing the least mean absolute error score of 0.015. Additionally, the model classifies patients into a valid group. Of the 429 records, 97 (out of 106), 99 (out of 119), 95 (out of 113), and 77 (out of 91) were classified to its correct label as stages - 1, 2, 3, and 4. The accuracy, recall, precision, and F-measure for each classification group obtained are 0.84, 0.85, 0.85, and 0.84. Conclusions: The study showed that aged patients with a higher number of mutations than young patients have a higher risk of short survival. Senior patients with a more significant number of mutations have an increased risk of getting into the last cancer stage.

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.

Algorithmic fairness in artificial intelligence for medicine and healthcare

In healthcare, the development and deployment of insufficiently fair systems of artificial intelligence (AI) can undermine the delivery of equitable care. Assessments of AI models stratified across subpopulations have revealed inequalities in how patients are diagnosed, treated and billed. In this Perspective, we outline fairness in machine learning through the lens of healthcare, and discuss how algorithmic biases (in data acquisition, genetic variation and intra-observer labelling variability, in particular) arise in clinical workflows and the resulting healthcare disparities. We also review emerging technology for mitigating biases via disentanglement, federated learning and model explainability, and their role in the development of AI-based software as a medical device.

A Comprehensive Pan-Cancer Analysis of the Tumorigenic Effect of Leucine-Zipper-Like Transcription Regulator (LZTR1) in Human Cancer

The elucidation of the action site, mechanism of Leucine-Zipper-like Transcription Regulator-1 (LZTR1) and its relationship with RAS-MAPK signaling pathway attracts more and more scholars to focus on the researches of LZTR1 and its role in tumorigenesis. However, there was no pan-cancer analysis between LZTR1 and human tumors reported before. Therefore, we are the first to investigate the potential oncogenic roles of LZTR1 across all tumor types based on the datasets of TCGA (The Cancer Genome Atlas) and GEO (Gene Expression Omnibus). LZTR1 plays a double-edged role in tumor development and prognosis. We found that the high expression of LZTR1 brings better outcomes in esophageal carcinoma (ESCA) and head and neck squamous cell carcinoma (HNSC) but brings worth outcomes in uveal melanoma (UVM), adrenocortical carcinoma (ACC), liver hepatocellular carcinoma (LIHC), and prostate adenocarcinoma (PRAD). Moreover, the expression of LZTR1 also strongly associated with pathological in ACC and bladder urothelial carcinoma (BLCA). We also found that the LZTR1 expression was associated with some immune cell infiltration including endothelial cells, regulatory T cells (Tregs), T cell CD8+, natural killer cells (NK cell), macrophages, neutrophil granulocyte, and cancer-associated fibroblasts in different cancers. Missense mutation in LZTR1 was detected in most cancers from TCGA datasets. Finally, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Body (GO) method was used to explain the pathogenesis of LZTR1. Our pan-cancer study provides a relatively comprehensive understanding of the carcinogenic role of LZTR1 in human tumors.

Genomic landscape of lung adenocarcinomas in different races

Background

Lung adenocarcinoma is a molecularly heterogeneous disease. Several studies, including The Cancer Genome Atlas Research Network (TCGA) and Lung Cancer Mutation Consortium (LCMC), explored the genetic alterations among different ethnic groups. However, minority groups are often under-represented in these relevant studies and the genomic alterations among racial groups are not fully understood.

Methods

We analyze genomic characteristics among racial groups to understand the diversities and their impact on clinical outcomes.

Results

Native Americans had significantly higher rates of insertions and deletions than other races (P<0.001). Among patients with lung adenocarcinomas, EGFR and KRAS were the highest discrepancy genes in the different racial groups (P<0.001). The EGFR exon 21 L858R point mutation was three times higher in Asians than in all other races (P<0.001). Asians, Whites, and Blacks had 4.7%, 3.1%, and 1.8% ALK rearrangement, respectively (P<0.001). White patients had the highest rates of reported KRAS G12C (15.51%) than other races (P<0.001). Whites (17.2%), Blacks (15.1%), and Other (15.7%) had higher rates of STK11 mutation than Asians (3.94%) (P<0.001). RET rearrangement and ERBB2 amplification were more common in Asian patients than in Other racial groups. Apart from point mutations, structural variations, and fusion genes, we identified a significant amount of copy number alterations in each race.

Conclusions

The tumor genomic landscape is significantly distinct in different races. This data would shed light on the understanding of molecular alterations and their impacts on clinical management in different lung cancer patients.

Demographic reporting across a decade of neuroimaging: a systematic review

Diversity of participants in biomedical research with respect to race, ethnicity, and biological sex is crucial, particularly given differences in disease prevalence, recovery, and survival rates between demographic groups. The objective of this systematic review was to report on the demographics of neuroimaging studies using magnetic resonance imaging (MRI). The Web of Science database was used and data collection was performed between June 2021 to November 2021; all articles were reviewed independently by at least two researchers. Articles utilizing MR data acquired in the United States, with n ≥ 10 human subjects, and published between 2010–2020 were included. Non-primary research articles and those published in journals that did not meet a quality control check were excluded. Of the 408 studies meeting inclusion criteria, approximately 77% report sex, 10% report race, and 4% report ethnicity. Demographic reporting also varied as function of disease studied, participant age range, funding, and publisher. We anticipate quantitative data on the extent, or lack, of reporting will be necessary to ensure inclusion of diverse populations in biomedical research.

Age influences on the molecular presentation of tumours

Cancer is often called a disease of aging. There are numerous ways in which cancer epidemiology and behaviour change with the age of the patient. The molecular bases for these relationships remain largely underexplored. To characterise them, we analyse age-associations in the nuclear and mitochondrial somatic mutational landscape of 20,033 tumours across 35 tumour-types. Age influences both the number of mutations in a tumour (0.077 mutations per megabase per year) and their evolutionary timing. Specific mutational signatures are associated with age, reflecting differences in exogenous and endogenous oncogenic processes such as a greater influence of tobacco use in the tumours of younger patients, but higher activity of DNA damage repair signatures in those of older patients. We find that known cancer driver genes such as CDKN2A and CREBBP are mutated in age-associated frequencies, and these alter the transcriptome and predict for clinical outcomes. These effects are most striking in brain cancers where alterations like SUFU loss and ATRX mutation are age-dependent prognostic biomarkers. Using three cancer datasets, we show that age shapes the somatic mutational landscape of cancer, with clinical implications.

JCGA: the Japanese version of the Cancer Genome Atlas and its contribution to the interpretation of gene alterations detected in clinical cancer genome sequencing

With the emergence of next-generation sequencing (NGS)-based cancer gene panel tests in routine oncological practice in Japan, an easily interpretable cancer genome database of Japanese patients in which mutational profiles are unaffected by racial differences is needed to improve the interpretation of the detected gene alterations. Considering this, we constructed the first Japanese cancer genome database, called the Japanese version of the Cancer Genome Atlas (JCGA), which includes multiple tumor types. The database includes whole-exome sequencing data from 4907 surgically resected primary tumor samples obtained from 4753 Japanese patients with cancer and graphically provides genome information on 460 cancer-associated genes, including the 336 genes that are included in two NGS-based cancer gene panel tests approved by the Pharmaceuticals and Medical Devices Agency. Moreover, most of the contents of this database are written in Japanese; this not only helps physicians explain the results of NGS-based cancer gene panel tests but also enables patients and their families to obtain further information regarding the detected gene alterations.

Bacterial Diversity Correlates with Overall Survival in Cancers of the Head and Neck, Liver, and Stomach

One in five cancers is attributed to infectious agents, and the extent of the impact on the initiation, progression, and disease outcomes may be underestimated. Infection-associated cancers are commonly attributed to viral, and to a lesser extent, parasitic and bacterial etiologies. There is growing evidence that microbial community variation rather than a single agent can influence cancer development, progression, response to therapy, and outcome. We evaluated microbial sequences from a subset of infection-associated cancers-namely, head and neck squamous cell carcinoma (HNSC), liver hepatocellular carcinoma (LIHC), and stomach adenocarcinoma (STAD) from The Cancer Genome Atlas (TCGA). A total of 470 paired tumor and adjacent normal samples were analyzed. In STAD, concurrent presence of EBV and Selemonas sputigena with a high diversity index were associated with poorer survival (HR: 2.23, 95% CI 1.26-3.94, p = 0.006 and HR: 2.31, 95% CI 1.1-4.9, p = 0.03, respectively). In LIHC, lower microbial diversity was associated with poorer overall survival (HR: 2.57, 95% CI: 1.2, 5.5, p = 0.14). Bacterial within-sample diversity correlates with overall survival in infection-associated cancers in a subset of TCGA cohorts.

Racial and ethnic disparities among children with primary central nervous system tumors in the US

INTRODUCTION

Primary central nervous system (CNS) tumors are among the most common and lethal types of cancer in children. However, the existence of health disparities in CNS tumors by race or ethnicity remains poorly understood. This systematic review sought to determine whether racial and ethnic disparities in incidence, healthcare access, and survival exist among pediatric patients diagnosed with CNS tumors.

METHODS

A search of MEDLINE, Embase, CINAHL, Web of Science, and Scopus was conducted. Inclusion criteria selected for studies published between January 1, 2005 and July 15, 2020 that focused on pediatric populations in the US, evaluated for potential differences based on racial or ethnic backgrounds, and focused on CNS tumors. A standardized study form was used to collect study information, population of interest, research design, and quality of analysis, sample size, participant demographics, pathology evaluated, and incidence or outcomes observed.

RESULTS

A total of 30 studies were inlcuded. Studies suggest White children may be more likely to be diagnosed with a CNS tumor and Hispanic children to present with advanced-stage disease and have worse outcomes. The degree of influence derived from socioeconomic factors is unclear. This review was limited by few available studies that included race and ethnicity as a variable, the overlap in databases used, and unclear categorization of race and ethnicity.

CONCLUSIONS

This review identified notable and at times contradicting variations in racial/ethnic disparities among children with CNS tumors, suggesting that the extent of these disparities remains largely unknown and prompts further research to improve health equity.

Immune-Based Cancer Treatment: Addressing Disparities in Access and Outcomes

Avoidable differences in the care and outcomes of patients with cancer (i.e., cancer care disparities) emerge or worsen with discoveries of new, more effective approaches to cancer diagnosis and treatment. The rapidly expanding use of immunotherapy for many different cancers across the spectrum from late to early stages has, predictably, been followed by emerging evidence of disparities in access to these highly effective but expensive treatments. The danger that these new treatments will further widen preexisting cancer care and outcome disparities requires urgent corrective intervention. Using a multilevel etiologic framework that categorizes the targets of intervention at the individual, provider, health care system, and social policy levels, we discuss options for a comprehensive approach to prevent and, where necessary, eliminate disparities in access to the clinical trials that are defining the optimal use of immunotherapy for cancer, as well as its safe use in routine care among appropriately diverse populations. We make the case that, contrary to the traditional focus on the individual level in descriptive reports of health care disparities, there is sequentially greater leverage at the provider, health care system, and social policy levels to overcome the challenge of cancer care and outcomes disparities, including access to immunotherapy. We also cite examples of effective government-sponsored and policy-level interventions, such as the National Cancer Institute Minority-Underserved Community Oncology Research Program and the Affordable Care Act, that have expanded clinical trial access and access to high-quality cancer care in general.

Geographic assessment of cancer genome profiling studies

Cancers arise from the accumulation of somatic genome mutations, which can be influenced by inherited genomic variants and external factors such as environmental or lifestyle-related exposure. Due to the heterogeneity of cancers, precise information about the genomic composition of germline and malignant tissues has to be correlated with morphological, clinical and extrinsic features to advance medical knowledge and treatment options. With global differences in cancer frequencies and disease types, geographic data is of importance to understand the interplay between genetic ancestry and environmental influence in cancer incidence, progression and treatment outcome. In this study, we analyzed the current landscape of oncogenomic screening publications for geographic information content and quality, to address underrepresented study populations and thereby to fill prominent gaps in our understanding of interactions between somatic variations, population genetics and environmental factors in oncogenesis. We conclude that while the use of proxy-derived geographic annotations can be useful for coarse-grained associations, the study of geo-correlated factors in cancer causation and progression will benefit from standardized geographic provenance annotations. Additionally, publication-derived geographic provenance data allowed us to highlight stark inequality in the geographies of cancer genome profiling, with a near lack of sizable studies from Africa and other large regions.

Biological Aspects of Cancer Health Disparities

Racial and ethnic disparities span the continuum of cancer care and are driven by a complex interplay among social, psychosocial, lifestyle, environmental, health system, and biological determinants of health. Research is needed to identify these determinants of cancer health disparities and to develop interventions to achieve cancer health equity. Herein, we focus on the overall burden of ancestry-related molecular alterations, the functional significance of the alterations in hallmarks of cancer, and the implications of the alterations for precision oncology and immuno-oncology. In conclusion, we reflect on the importance of estimating ancestry, improving diverse racial and ethnic participation in cancer clinical trials, and examining the intersection among determinants of cancer health disparities.

Tumor Mutation Burden Predicts Relapse in Papillary Thyroid Carcinoma With Changes in Genes and Immune Microenvironment

BACKGROUND

The risk factors of papillary thyroid carcinoma (PTC) recurrence are meaningful for patients and clinicians. Tumor mutation burden (TMB) has been a biomarker for the effectiveness of immune checkpoint inhibitor (ICI) and prognosis in cancer. However, the role of TMB and its latent significance with immune cell infiltration in PTC are still unclear. Herein, we aimed to explore the effect of TMB on PTC prognosis.

MATERIAL AND METHODS

RNA-seq and DNA-seq datasets of PTC patients were downloaded from The Cancer Genome Atlas (TCGA) database. The Gene Ontology (GO) and gene set enrichment analysis (GSEA 4.0.1) were applied further to explore potential differences in PTC patients' biological functions. The differentially expressed genes (DEGs) and immune microenvironment between the high and low TMB groups were determined.

RESULTS

TMB had the highest AUC score than other clinical indicators in ROC analysis on recurrence-free survival, and a higher TMB score was related to a worse prognosis. Further, GSEA showed a higher level of oxidative phosphorylation (OXPHOS) in the high TMB group, and four genes correlated with recurrence-free survival rate were identified. The abundance of CD8⁺ T cells and M1 macrophages in the high TMB group was significantly lower than that in the low TMB group.

CONCLUSIONS

Our study found that TMB was a better predictor variable at evaluating the risk of PTC recurrence. Moreover, TMB-related genes conferred dramatically correlated prognosis, which was worth exploring in guiding postoperative follow-up and predicting recurrence for PTC patients.

Genetic alterations associated with 18F-fluorodeoxyglucose positron emission tomography/computed tomography in head and neck squamous cell carcinoma

•

¹⁸F-FDG PET/CT visualizes altered glucose metabolism which is underpinned by the alteration of specific genes and signaling pathways.

•

Our analysis of TCGA-HNSC data showed a positive correlation of FDG uptake with the total and non-silent mutation rates, genetic heterogeneity, and copy number alterations.

•

Significant higher FDG uptake was noted in patients with alterations in cell cycle (CDKN2A gene), or TP53 oncogenic signaling pathways (TP53 gene).

Background

We investigated the relationship between genetic alterations and ¹⁸F-FDG PET/CT findings in head and neck squamous cell carcinoma (HNSC).

Methods

Using mRNA-sequences of HNSC samples (480 patients) from the Cancer Genome Atlas (TCGA) portal, gene coexpression networks were constructed via a weighted correlation network analysis (WGCNA) algorithm, and their association with the tumor-to-blood signal ratio on ¹⁸F-FDG PET/CT data (21 patients) was explored. An elastic-net regression model was developed to estimate the PET tumor-to-blood ratio from the gene networks and to derive an FDG signature score (FDG_SS). The FDG_SS was evaluated with regard to clinical variables and general mutational profiles, as well as alterations to oncogenic signaling pathways.

Findings

The FDG_SS values differed across clinical stages (p = 0.027), HPV-status (p< 0.001), and molecular subtypes of HNSC (p< 0.001). Multivariate Cox regression demonstrated that FDG_SS was an independent predictor for overall (p = 0.019) and progression-free survival (p = 0.024). FDG_SS positively correlated with total mutation rate (p = 0.016), aneuploidy (p < 0.001), and somatic copy number alteration scores (p < 0.001). CDKN2A in the cell cycle pathway (q = 0.014) and the TP53 gene in the TP53 pathway (q = 0.005) showed significant differences between high and low FDG_SS patients.

Conclusion

FDG_SS based on the gene coexpression network was associated with the mutational landscape of HNSC. ¹⁸F-FDG PET/CT is therefore a valuable tool for the in vivo imaging of these cancers, being able to visualize the glucose metabolism of the tumor and allow inferences to be made on the underlying genetic alterations in the tumor.

Differential mutation spectrum and immune landscape in African Americans versus Whites: A possible determinant to health disparity in head and neck cancer

African Americans (AA) with Head and Neck Squamous Cell Carcinoma (HNSCC) have a worse disease prognosis than White patients despite adjusting for socio-economic factors, suggesting the potential biological contribution. Therefore, we investigated the genomic and immunological components that drive the differential tumor biology among race. We utilized the cancer genome atlas and cancer digital archive of HNSCC patients (1992-2013) for our study. We found that AA patients with HNSCC had a higher frequency of mutation compared to Whites in the key driver genes-P53, FAT1, CASP8 and HRAS. AA tumors also exhibited lower intratumoral infiltration of effector immune cells (CD8+, γδT, resting memory CD4+ and activated memory CD4+ T cells) with shorter survival than Whites. Unsupervised hierarchical clustering of differentially expressed genes demonstrated distinct gene clusters between AA and White patients with unique signaling pathway enrichments. Connectivity map analysis identified drugs (Neratinib and Selumetinib) that target aberrant PI3K/RAS/MEK signaling and may reduce racial disparity in therapy response.

Analysis of Heterogeneity in Survival Benefit of Immunotherapy in Oncology According to Patient Demographics and Performance Status: A Systematic Review and Meta-Analysis of Overall Survival Data

OBJECTIVES

Immunotherapy (IO) has become standard of care (SOC) for many advanced malignancies, although identifying patients likely to benefit remains difficult. We sought to assess whether demographic factors are associated with response to IO, compared with SOC systemic therapy, using stratified meta-analysis.

METHODS

A systematic review of MEDLINE, PubMed, Embase, and Scopus from inception to October 2, 2018. Randomized controlled trials comparing IO to SOC in patients with advanced solid organ malignancies were included if results were stratified by age, performance status (PS), or race, assessing overall survival (OS). Pooled hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated for each group using random-effects models independently.

RESULTS

We identified 21 eligible randomized controlled trials, including 20 stratified by age, 17 by PS, and 4 by race. Patients with PS 0 (HR, 0.74; 95% CI, 0.63-0.86) and PS≥1 (HR, 0.75; 95% CI, 0.68-0.83) had similar OS benefits from IO compared with SOC (P=0.80). There was no difference on the basis of patient race (white vs. nonwhite) (P=0.46). IO demonstrated an OS benefit for younger (below 65 y: HR, 0.73; 95% CI, 0.65-0.82) and older (65 y and above: HR, 0.79; 95% CI, 0.71-0.88) patients with no difference between age groups (P=0.27). Among prespecified subgroup analyses, there was significant effect modification in 2 subgroups: younger patients in the first-line setting (P=0.03) and those receiving anti-CTLA-4 drugs (P=0.05).

CONCLUSIONS

When examining OS using stratified meta-analysis, we did not demonstrate significant differences in IO efficacy according to patient age, PS or race, though data on race were sparse.

Enabling population assignment from cancer genomes with SNP2pop

In many cancers, incidence, treatment efficacy and overall prognosis vary between geographic populations. Studies disentangling the contributing factors may help in both understanding cancer biology and tailoring therapeutic interventions. Ancestry estimation in such studies should preferably be driven by genomic data, due to frequently missing or erroneous self-reported or inferred metadata. While respective algorithms have been demonstrated for baseline genomes, such a strategy has not been shown for cancer genomes carrying a substantial somatic mutation load. We have developed a bioinformatics tool for the assignment of population groups from genome profiling data for both unaltered and cancer genomes. Despite extensive somatic mutations in the cancer genomes, consistency between germline and cancer data reached of 97% and 92% for assignment into 5 and 26 ancestral groups, respectively. Comparison with self-reported meta-data estimated a matching rate between 88-92%, mostly limited by interpretation of self-reported ethnicity labels compared to the standardized mapping output. Our SNP2pop application allows to assess population information from SNP arrays as well as sequencing platforms and to estimate the population structure in cancer genomics projects, to facilitate research into the interplay between ethnicity-related genetic background, environmental factors and somatic mutation patterns in cancer biology.

The evolution of resistance and tolerance as cancer defences

Although there is a plethora of cancer associated-factors that can ultimately culminate in death (cachexia, organ impairment, metastases, opportunistic infections, etc.), the focal element of every terminal malignancy is the failure of our natural defences to control unlimited cell proliferation. The reasons why our defences apparently lack efficiency is a complex question, potentially indicating that, under Darwinian terms, solutions other than preventing cancer progression are also important contributors. In analogy with host-parasite systems, we propose to call this latter option ‘tolerance’ to cancer. Here, we argue that the ubiquity of oncogenic processes among metazoans is at least partially attributable to both the limitations of resistance mechanisms and to the evolution of tolerance to cancer. Deciphering the ecological contexts of alternative responses to the cancer burden is not a semantic question, but rather a focal point in understanding the evolutionary ecology of host-tumour relationships, the evolution of our defences, as well as why and when certain cancers are likely to be detrimental for survival.

Tumor mutational burden in lung cancer: a systematic literature review

Purpose: To assess the association of tumor mutational burden (TMB) with clinical outcomes, other biomarkers and patient/disease characteristics in patients receiving therapy for lung cancer. Results: In total, 4,303 publications were identified; 81 publications were included. The majority of publications assessing clinical efficacy of immunotherapy reported an association with high TMB, particularly when assessing progression-free survival and objective response rate. High TMB was consistently associated with TP53 alterations, and negatively associated with EGFR mutations. High TMB was also associated with smoking, squamous cell non-small cell lung carcinoma, and being male. Methods: A systematic literature review based upon an a priori protocol was conducted following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Cochrane methodologies. Searches were conducted in EMBASE, SCOPUS, Ovid MEDLINE®, and Emcare (from January 2012 until April 2018) and in two clinical trial registries. Conference abstracts were identified in EMBASE, and in targeted searches of recent major conference proceedings (from January 2016 until April 2018). Publications reporting data in patients receiving therapy for lung cancer that reported TMB and its association with clinical efficacy, or with other biomarkers or patient/disease characteristics, were included. Results are presented descriptively. Conclusion: This systematic literature review identified several clinical outcomes, biomarkers, and patient/disease characteristics associated with high TMB, and highlights the need for standardized definitions and testing practices. Further studies using standardized methodology are required to inform treatment decisions.

The prognostic value of tumor mutation burden in EGFR-mutant advanced lung adenocarcinoma, an analysis based on cBioPortal data base

Background

Tumor mutation burden (TMB) is novel biomarker of promising predict value in prediction of immune checkpoint inhibitors (ICPis) in non-small cell lung cancer (NSCLC). However, the distribution of TMB in epidermal growth factor receptor (EGFR)-mutant advanced lung adenocarcinoma (LUAD) patients and the impact on overall survival (OS) time are not well demonstrated.

Methods

Information regarding gene mutations and patients' survival time in advanced LUAD was downloaded from The Cancer Genome Atlas (TCGA) database. The diversity of TMB in different EGFR-mutant types was observed and the predicted value of TMB for OS as well as other co-mutations were analyzed. The diversity of TMB was also observed in another Chinese cohort of advanced LUAD patients.

Results

The median TMB values of EGFR wild-type, other types of EGFR mutations, exon 19 deletions and L858R were 6.12, 5.66, 3.77 and 4.72, differences between wild-type and EGFR sensitive mutations (exon 19 deletion or L858R) were significant (P<0.001 and P<0.01). OS time of high TMB group was inferior to that of the low TMB group (24.03 months vs. not reached, P=0.0020). TMB and TP53 together will make more accurate prediction of OS in EGFR-mutant advanced LUAD patients. Distribution of TMB in another Chinese cohort had the same trend.

Conclusions

In advanced LUAD patients, TMB was lower in patients with EGFR-mutant group than EGFR wild group. TMB was a negative prognostic biomarker of OS in EGFR-mutant LUAD patients, especially when TP53 was mutated together.

Distribution differences in prognostic copy number alteration profiles in IDH-wild-type glioblastoma cause survival discrepancies across cohorts

The diagnosis and prognostication of glioblastoma (GBM) remain to be solely dependent on histopathological findings and few molecular markers, despite the clinical heterogeneity in this entity. To address this issue, we investigated the prognostic impact of copy number alterations (CNAs) using two population-based IDH-wild-type GBM cohorts: an original Japanese cohort and a dataset from The Cancer Genome Atlas (TCGA). The molecular disproportions between these cohorts were dissected in light of cohort differences in GBM. The Japanese cohort was collected from cases registered in Kansai Molecular Diagnosis Network for CNS tumors (KNBTG). The somatic landscape around CNAs was analyzed for 212 KNBTG cases and 359 TCGA cases. Next, the clinical impacts of CNA profiles were investigated for 140 KNBTG cases and 152 TCGA cases treated by standard adjuvant therapy using temozolomide-based chemoradiation. The comparative profiling indicated unequal distribution of specific CNAs such as EGFR, CDKN2A, and PTEN among the two cohorts. Especially, the triple overlap CNAs in these loci (triple CNA) were much higher in frequency in TCGA (70.5%) than KNBTG (24.3%), and its prognostic impact was independently validated in both cohorts. The KNBTG cohort significantly showed better prognosis than the TCGA cohort (median overall survival 19.3 vs 15.6 months). This survival difference between the two cohorts completely resolved after subclassifying all cases according to the triple CNA status. The prognostic significance of triple CNA was identified in IDH-wild-type GBM. Distribution difference in prognostic CNA profiles potentially could cause survival differences across cohorts in clinical studies.

Immunometabolic Alterations by HPV Infection: New Dimensions to Head and Neck Cancer Disparity

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer, with high morbidity and mortality. Racial disparity in HNSCC is observed between African Americans (AAs) and whites, effecting both overall and 5-year survival, with worse prognosis for AAs. In addition to socio-economic status and demographic factors, many epidemiological studies have also identified factors including coexisting human papillomavirus (HPV) infection, primary tumor location, and a variety of somatic mutations that contribute to the prognostic incongruities in HNSCC patients among AAs and whites. Recent research also suggests HPV-induced dysregulation of tumor metabolism and immune microenvironment as the major regulators of HNSCC patient prognosis. Outcomes of several preclinical and clinical studies on targeted therapeutics warrant the need to elucidate the inherent mechanistic and population-based disparities underlying patient responses. This review systematically reports the underlying reasons for inconsistency in disease prognosis and therapy responses among HNSCC patients from different racial populations. The focus of this review is twofold: aside from discussing the causes of racial disparity, we also seek to identify the consequences of such disparity in terms of HPV infection and its associated mutational, metabolic, and immune landscapes. Considering the clinical impact of differential patient outcomes among AA and white populations, understanding the underlying cause of this disparity may pave the way for novel precision therapy for HNSCC.

Integrated analysis of transcription factors and targets co-expression profiles reveals reduced correlation between transcription factors and target genes in cancer

Transcription factors are recognized as the key regulators of gene expression. However, the changes in the correlation of transcription factors and their target genes between normal and tumor tissues are usually ignored. In this research, we used mRNA expression profile data from The Cancer Genome Atlas which included 5726 samples across 11 major human cancers to perform co-expression analysis by the Pearson correlation coefficients. Then, integrating 81,357 pairs of transcription factors and target genes from transcription factors databases to find out the changes in the co-expression correlation of these gene pairs from normal to tumor tissues. Based on the changes in the number of co-expressed TF-TG pairs and changes in the level of co-expression, we found the generally reduced correlation between transcription factors and their target genes in cancer. Additionally, we screened out universal and specific transcription factors-target genes pairs which may significant influence particular cancer. Then, we obtained 423 cancer cell line expression profiles from Broad Institute Cancer Cell Line Encyclopedia to verify our results. Some of these pairs like XRCC5-XRCC6 have been reported to involve in multiple cancers, while pairs like IRF1-PSMB9 without any previous articles related to tumor but involve in the biological processes of cancer, which are of great potential to be therapeutic targets. Our research may provide insights to better understand the tumor development mechanisms and find potential therapeutic targets.

Global Inequities in Precision Medicine and Molecular Cancer Research

Precision medicine based upon molecular testing is heralded as a revolution in how cancer is prevented, diagnosed, and treated. Large efforts across the world aim to conduct comprehensive molecular profiling of disease to inform preclinical models, translational research studies and clinical trials. However, most studies have only been performed in patients from high-income countries. As the burden on non-communicable diseases increases, cancer will become a pressing burden across the world, disproportionately affecting low-middle income settings. There is emerging evidence that the molecular landscape of disease differs geographically and by genetic ancestry, which cannot be explained by environmental factors alone. There is a lack of good quality evidence that characterises the molecular landscape of cancers found in low-middle income countries. As cancer medicine becomes increasingly driven by molecular alterations in high-income settings, low-income settings may become left behind. Further efforts on an international scale must be made by researchers, funders, and policymakers to ensure cancer research addresses disease across the world, so models are not limited to subtypes of disease found in high-income countries. In this review, we discuss differences found in the molecular profiles of tumours worldwide and the implication this has for the future of global cancer care. Finally, we identify several barriers currently limiting progress in this field and innovative solutions, which may address these shortcomings.

Survival analysis in Caucasian pulmonary adenocarcinoma patients based on differential targets between Caucasian and Asian population

Ethnicity differences may contribute to the variety of overall survival in pulmonary adenocarcinoma, while the influence of ethnicity relevant somatic driver mutations (ERSDM) profile on Caucasian survival is not well investigated. In this study, we studied epidermal growth factor receptor (EGFR), tumor protein p53 (TP53), Kirsten rat sarcoma 2 viral oncogene homolog (KRAS), and Serine/Threonine Kinase 11 (STK11) to construct the ERSDM profile. Those genes were selected as harboring somatic driver mutations with >10% prevalence and with different occurrence between Caucasian and Asian ethnicity. Clinical information and transcriptome sequencing of 173 Caucasian pulmonary adenocarcinoma patients with matched mutation data are retrieved from TCGA, Kaplan-Meier analyses and Cox proportional-hazards regression models are further used to analyze the effect of the ERSDM profile on overall survival. There is no significant correlation between single gene mutation and overall survival, while patients with less than two mutated genes have a better overall survival compared with those with at least two mutated genes (p = 0.034). All of these indicate that multiple mutations in the ERSDM profile may be a negative prognostic factor for overall survival in Caucasian pulmonary adenocarcinoma patients.