Characterization of tumors utilizing next-generation sequencing methods, including assessment of the number of somatic mutations (tumor mutational burden [TMB]), is currently at the forefront of the field of personalized medicine. Recent clinical studies have associated high TMB with improved patient response rates and survival benefit from immune checkpoint inhibitors; hence, TMB is emerging as a biomarker of response for these immunotherapy agents. However, variability in current methods for TMB estimation and reporting is evident, demonstrating a need for standardization and harmonization of TMB assessment methodology across assays and centers. Two uniquely placed organizations, Friends of Cancer Research (Friends) and the Quality Assurance Initiative Pathology (QuIP), have collaborated to coordinate efforts for international multistakeholder initiatives to address this need. Friends and QuIP, who have partnered with several academic centers, pharmaceutical organizations, and diagnostic companies, have adopted complementary, multidisciplinary approaches toward the goal of proposing evidence-based recommendations for achieving consistent TMB estimation and reporting in clinical samples across assays and centers. Many factors influence TMB assessment, including preanalytical factors, choice of assay, and methods of reporting. Preliminary analyses highlight the importance of targeted gene panel size and composition, and bioinformatic parameters for reliable TMB estimation. Herein, Friends and QuIP propose recommendations toward consistent TMB estimation and reporting methods in clinical samples across assays and centers. These recommendations should be followed to minimize variability in TMB estimation and reporting, which will ensure reliable and reproducible identification of patients who are likely to benefit from immune checkpoint inhibitors.

The causes underlying racial disparities in cancer are multifactorial. In addition to socioeconomic issues, biological factors may contribute to these inequities, especially in disease incidence and patient survival. To date, there have been few studies that relate the disparities in these aspects to genetic aberrations. In this work, we studied the impacts of race on the patient survival and tumor mutation burden using the data released by the Cancer Genome Atlas (TCGA). The potential relationship between mutation burden and disease incidence is further inferred by an integrative analysis of TCGA data and the data from the Surveillance, Epidemiology, and End Results (SEER) Program. The results show that disparities are present (p < 0.05) in patient survival of five cancers, such as head and neck squamous cell carcinoma. The numbers of tumor driver mutations are differentiated (p < 0.05) over the racial groups in five cancers, such as lung adenocarcinoma. By treating a specific cancer type and a racial group as an "experimental unit", driver mutation numbers demonstrate a significant (r = 0.46, p < 0.002) positive correlation with cancer incidence rates, especially when the five cancers with mutational disparities are exclusively focused (r = 0.88, p < 0.00002). These results enrich our understanding of racial disparities in cancer and carcinogenic process.

Osteosarcoma (OTS) is aggressive bone malignancy without well-recognized prognosis biomarker. Tumor mutational burden (TMB) has been proved as effective biomarker in predicting clinical outcomes in several cancer types. However, its prognostic value in OTS remains unknown. In this study, we aim to evaluate the implication of TMB in OTS patients.

Sophorolipids (SL) are amphiphilic biosurfactant molecules consisting of a disaccharide sophorose with one fatty acid at the C1 position and optional acetylation at the C6'and C6" positions. They exist in a closed ring lactonic (LSL) or open acidic (ASL) structure Sophorolipids are produced in crude mixtures in economically viable amounts by the yeast Starmerella bombicola and used in a variety of consumer products. Varying levels of anti- proliferative and anti-cancer activity of crude sophorolipid mixtures are described in a number of tumor cell lines in vitro. However, significant inter-study variation exists in the composition of sophorolipid species as well as other biologically active compounds in these mixtures, which makes interpretation of in vitro and in vivo studies difficult. We produced a 96% pure C18:1 lactonic sophorolipid that dose-dependently reduces the viability of colorectal cancer, as well as normal human colonic and lung cell lines in vitro. Oral administration of vehicle-only; or lactonic sophorolipids (50 mg/kg for 70 days), to Apcmin+/- mice resulted in an increase in the number (55.5 ± 3.3 vs 70.50 ± 7.8: p < 0.05) and size (modal size 2mm vs 4mm) of intestinal polyps. Lactonic administration resulted in a systematic effect via reduced hematocrit (49.5 ± 1.0 vs 28.2 ± 2.0 vs: p<0.03) and splenomegaly (0.56 ± 0.03g vs 0.71 ± 0.04g; p<0.01) confirming exacerbation of disease progression in this model.

Several immune checkpoint inhibitors (ICIs) have already been introduced into clinical practice or are in advanced phases of clinical experimentation. Extensive efforts are being made to identify robust biomarkers to select patients who may benefit from treatment with ICIs. Tumor mutation burden (TMB) may be a relevant biomarker of response to ICIs in different tumor types; however, its clinical use is challenged by the analytical methods required for its evaluation. The possibility of using targeted next-generation sequencing panels has been investigated as an alternative to the standard whole exome sequencing approach. However, no standardization exists in terms of genes covered, types of mutations included in the estimation of TMB, bioinformatics pipelines for data analysis, and cut-offs used to discriminate samples with high, intermediate or low TMB. Bioinformatics serve a relevant role in the analysis of targeted sequencing data and its standardization is essential to deliver a reliable test in clinical practice. In the present study, cultured and formalin-fixed, paraffin-embedded cell lines were analyzed using a commercial panel for TMB testing; the results were compared with data from the literature and public databases, demonstrating a good correlation. Additionally, the correlation between high tumor mutation burden and microsatellite instability was confirmed. The bioinformatics analyses were conducted using two different pipelines to highlight the challenges associated with the development of an appropriate analytical workflow.

With the recent FDA approval of tumor mutational burden-high (TMB-H) status as a biomarker for treatment with a PD-1 inhibitor regardless of tumor type, accurate assessment of patient-specific TMB is more critical now more than ever. Using paired tumor and germline exome sequencing data from 701 patients newly diagnosed with multiple myeloma, including 575 self-reported White patients and 126 self-reported Black patients, we observed that compared to the gold standard of filtering germline variants with patient-paired germline sequencing data, TMB estimates were significantly higher in both Black and White patients when using public databases for filtering non-somatic mutations; however, TMB was more significantly inflated in Black patients compared to White patients. TMB as a biomarker for patient selection to receive immune checkpoint inhibitors (ICIs) therapy without patient-paired germline sequencing may introduce racial bias due to the under-representation of minority groups in public databases.

Immune checkpoint blockade (ICB) is becoming standard-of-care in many types of human malignancies, but patient selection is still imperfect. Tumor mutation burden (TMB) is being evaluated as a biomarker for ICB in clinical trials, but most of the sequencing panels used to estimate it are inadequately designed. Here, we present a bioinformatics-based method to select panels and mathematical models for accurate TMB prediction. Our method is based on tumor-specific, forward-step selection of genes, generation of panels using a linear regression algorithm, and rigorous internal and external validation comparing predicted with experimental TMB. As a result, we propose cancer-specific panels for 14 malignancies which can offer reliable, clinically relevant estimates of TMBs. Our work facilitates a better prediction of TMB that can improve the selection of patients for ICB therapy.

Whether tumor mutational burden (TMB) is related to improved survival outcomes or the promotion of immunotherapy in various malignant tumors remains controversial, and we lack a comprehensive understanding of TMB across cancers. Based on the data obtained from The Cancer Genome Atlas (TCGA), we conducted a multiomics analysis of TMB across 21 cancer types to identify characteristics related to TMB and determine the mechanism as it relates to prognosis, gene expression, gene mutation and signaling pathways. In our study, TMB was found to have a significant relationship with prognosis for 21 tumors, and the relationship was different in different tumors. TMB may also be related to different outcomes for patients with different tumor subtypes. TMB was confirmed to be correlated with clinical information, such as age and sex. Mutations in GATA3 and MAP3K1 in beast invasive carcinoma (BRCA), TCF7L2 in colon adenocarcinoma (COAD), NFE2L2 in esophageal carcinoma (ESCA), CIC and IDH1 in brain lower grade glioma (LGG), CDH1 in stomach adenocarcinoma (STAD), and TP53 in uterine corpus endometrial carcinoma (UCEC) were demonstrated to be correlated with lower TMB. Moreover, we identified differentially expressed genes (DEGs) and differentially methylated regions (DMRs) according to different TMB levels in 21 cancers. We also investigated the correlation between enrichment of signaling pathways, immune cell infiltration and TMB. In conclusion, we identified multiomic characteristics related to the TMB in 21 tumors, providing support for a comprehensive understanding of the role of TMB in different tumors.

Tumor mutation burden is an imperfect proxy of tumor foreignness and has therefore failed to consistently demonstrate clinical utility in predicting responses in the context of immunotherapy. We evaluated mutations in regions of the genome that are unlikely to undergo loss in a pan-cancer analysis across 31 tumor types (n = 9,242) and eight immunotherapy-treated cohorts of patients with non-small-cell lung cancer, melanoma, mesothelioma, and head and neck cancer (n = 524). We discovered that mutations in single-copy regions and those present in multiple copies per cell constitute a persistent tumor mutation burden (pTMB) which is linked with therapeutic response to immune checkpoint blockade. Persistent mutations were retained in the context of tumor evolution under selective pressure of immunotherapy and tumors with a high pTMB content were characterized by a more inflamed tumor microenvironment. pTMB imposes an evolutionary bottleneck that cancer cells cannot overcome and may thus drive sustained immunologic tumor control in the context of immunotherapy.

Breast cancer cells frequently home to the bone, but the mechanisms controlling tumor colonization of the bone marrow remain unclear. We report significant enrichment of bone-disseminated estrogen receptor positive human MCF7 cells by 17 β-estradiol (E2) following intracardiac inoculation. Using flow cytometric and quantitative PCR approaches, tumor cells were detected in >80% of MCF7 tumor-inoculated mice, regardless of E2, suggesting that E2 is not required for MCF7 dissemination to the bone marrow. Furthermore, we propose two additional models in which to study prolonged latency periods by bone-disseminated tumor cells: murine D2.0R and human SUM159 breast carcinoma cells. Tumor cells were detected in bone marrow of up to 100% of D2.0R and SUM159-inoculated mice depending on the detection method. These findings establish novel models of bone colonization in which to study mechanisms underlying tumor cell seeding to the marrow and prolonged latency, and provide highly sensitive methods to detect these rare events.

Spontaneous canine cancers are valuable but relatively understudied and underutilized models. To enhance their usage, we reanalyze whole exome and genome sequencing data published for 684 cases of >7 common tumor types and >35 breeds, with rigorous quality control and breed validation. Our results indicate that canine tumor alteration landscape is tumor type-dependent, but likely breed-independent. Each tumor type harbors major pathway alterations also found in its human counterpart (e.g., PI3K in mammary tumor and p53 in osteosarcoma). Mammary tumor and glioma have lower tumor mutational burden (TMB) (median < 0.5 mutations per Mb), whereas oral melanoma, osteosarcoma and hemangiosarcoma have higher TMB (median ≥ 1 mutations per Mb). Across tumor types and breeds, TMB is associated with mutation of TP53 but not PIK3CA, the most mutated genes. Golden Retrievers harbor a TMB-associated and osteosarcoma-enriched mutation signature. Here, we provide a snapshot of canine mutations across major tumor types and breeds.

Tumor mutation burden (TMB) is an emerging factor associated with survival with immunotherapy. When tumor-normal pairs are available, TMB is determined by calculating the difference between somatic and germline sequences. In the case of commonly used tumor-only sequencing, additional steps are needed to estimate the somatic alterations. Computational tools have been developed to determine germline contribution based on sample copy state, purity estimates, and occurrence of the variant in population databases; however, there is potential for sampling bias in population data sets.

Tumor mutational burden (TMB) could be a measure of response to immune checkpoint inhibitors therapy for patients with colorectal cancer (CRC). MicroRNAs (miRNAs) participate in anticancer immune responses. In the present study, we determined miRNA expression patterns in patients with CRC and built a signature that predicts TMB.

Tumor mutational burden (TMB), measured by exome or panel sequencing of tumor tissue or blood (bTMB), is a potential predictive biomarker for treatment benefit in patients with various cancer types receiving immunotherapy targeting checkpoint pathways. However, significant variability in TMB measurement has been observed. We developed contrived bTMB reference materials using DNA from tumor cell lines and donor-matched lymphoblastoid cell lines to support calibration and alignment across laboratories and platforms. Contrived bTMB reference materials were developed using genomic DNA from lung tumor cell lines blended into donor-matched lymphoblastoid cell lines at 0.5% and 2% tumor content, fragmented and size-selected to mirror the size profile of circulating cell-free tumor DNA with TMB scores of 7, 9, 20, and 26 mut/Mb. Variant allele frequency (VAF) and bTMB scores were assessed using PredicineATLAS and GuardantOMNI next-generation sequencing assays. DNA fragment sizes in the contrived reference samples were similar to those found within patient plasma-derived cell-free DNA, and mutational patterns aligned with those in the parental tumor lines. For the 7, 20, and 26 mut/Mb contrived reference samples with 2% tumor content, bTMB scores estimated using either assay aligned with expected scores from the parental tumor cell lines and showed good reproducibility. A bioinformatic filtration step was required to account for low-VAF artifact variants. We demonstrate the feasibility and challenges of producing and using bTMB reference standards across a range of bTMB levels, and how such standards could support the calibration and validation of bTMB platforms and help harmonization between panels and laboratories.

Fas, a member of the tumor necrosis family, is responsible for initiating the apoptotic pathway when bound to its ligand, Fas-L. Defects in the Fas-mediated apoptotic pathway have been reported in colorectal cancer.

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.

Merkel cell carcinoma (MCC) is a rare and highly aggressive cutaneous neuroendocrine carcinoma with increasing incidence. Cytotoxic chemotherapy and checkpoint inhibitors provide treatment options in the metastatic setting; however, there are no approved or standard of care targeted therapy treatment options.

Accurate estimation of systemic tumor load from the blood of cancer patients has enormous potential. One avenue is to measure the presence of cell-free circulating tumor DNA in plasma. Various approaches have been investigated, predominantly covering hotspot mutations or customized, patient-specific assays. Therefore, we investigated the utility of using exome sequencing to monitor circulating tumor DNA levels through the detection of single nucleotide variants in plasma. Two technologies, claiming to offer efficient library preparation from nanogram levels of DNA, were evaluated. This allowed us to estimate the proportion of starting molecules measurable by sequence capture (<5%). As cell-free DNA is highly fragmented, we designed and provide software for efficient identification of PCR duplicates in single-end libraries with a varying size distribution. On average, this improved sequence coverage by 38% in comparison to standard tools. By exploiting the redundant information in PCR-duplicates the background noise was reduced to ∼1/35,000. By applying our optimized analysis pipeline to a simulation analysis, we determined the current sensitivity limit to ∼1/2400, starting with 30 ng of cell-free DNA. Subsequently, circulating tumor DNA levels were assessed in seven breast- and one prostate cancer patient. One patient carried detectable levels of circulating tumor DNA, as verified by break-point specific PCR. These results demonstrate exome sequencing on cell-free DNA to be a powerful tool for disease monitoring of metastatic cancers. To enable a broad implementation in the diagnostic settings, the efficiency limitations of sequence capture and the inherent noise levels of the Illumina sequencing technology must be further improved.

In pancreatic cancer (PC), Tumor mutation burden (TMB) has been reported to be lower than in other cancers, with its clinical significance remaining unclear. We analyzed the dataset of whole-exome sequencing and gene expression profiling of 93 resected PC cases. The median TMB was 0.24. The TMB was classified as High (≥ 5.0), Low (< 5.0, ≥ 1.0), or Ultra-low (< 1.0). Nineteen samples (20%) were classified as TMB-low, and 74 (80%) were classified as TMB-ultra-low; no samples were TMB-high. TMB-ultra-low PC had significantly fewer borderline resectable lesions (P = 0.028) and fewer adenosquamous carcinomas (P = 0.003) than TBM-low PC. Furthermore, the TMB-ultra-low PC showed significantly lower detection rates of driver mutations and copy number variations. Microsatellite instability was not significantly correlated with the TMB status. The TMB-ultra-low PC had a significantly better prognosis than TBM-low PC (P = 0.023). A multivariate analysis identified TMB-ultra-low PC as an independent favorable prognostic factor (hazard ratio, 2.11; P = 0.019). A gene expression analysis showed that TMB-ultra-low PC was associated with reduced TP53 inactivation (P = 0.003) and reduced chromosomal instability (P = 0.001) compared to TBM-low PC. TMB-ultra-low PC had specific gene expression signatures and a better prognosis than TMB-low PC.

Tumor mutation burden has been proven to be a good predictor for the efficacy of immunotherapy, especially in patients with hypermutation. However, most research focused on the analysis of hypermutation in individual tumors, and there is a lack of integrated research on the hypermutation across different cancers. This study aimed to characterize hypermutated patients to distinguish between these patients and non-hypermutated patients.