Emerging therapeutic strategies for metastatic uveal melanoma: Targeting driver mutations

Uveal melanoma (UM) is the most common primary malignant intraocular tumor in adults. Although primary UM can be effectively controlled, a significant proportion of cases (40% or more) eventually develop distant metastases, commonly in the liver. Metastatic UM remains a lethal disease with limited treatment options. The initiation of UM is typically attributed to activating mutations in GNAQ or GNA11. The elucidation of the downstream pathways such as PKC/MAPK, PI3K/AKT/mTOR, and Hippo-YAP have provided potential therapeutic targets. Concurrent mutations in BRCA1 associated protein 1 (BAP1) or splicing factor 3b subunit 1 (SF3B1) are considered crucial for the acquisition of malignant potential. Furthermore, in preclinical studies, actionable targets associated with BAP1 loss or oncogenic mutant SF3B1 have been identified, offering promising avenues for UM treatment. This review aims to summarize the emerging targeted and epigenetic therapeutic strategies for metastatic UM carrying specific driver mutations and the potential of combining these approaches with immunotherapy, with particular focus on those in upcoming or ongoing clinical trials.

Whole-genome mapping of APOBEC mutagenesis in metastatic urothelial carcinoma identifies driver hotspot mutations and a novel mutational signature

Apolipoprotein B mRNA-editing enzyme catalytic polypeptide-like (APOBEC) enzymes mutate specific DNA sequences and hairpin-loop structures, challenging the distinction between passenger and driver hotspot mutations. Here, we characterized 115 whole genomes of metastatic urothelial carcinoma (mUC) to identify APOBEC mutagenic hotspot drivers. APOBEC-associated mutations were detected in 92% of mUCs and were equally distributed across the genome, while APOBEC hotspot mutations (ApoHMs) were enriched in open chromatin. Hairpin loops were frequent targets of didymi (twins in Greek), two hotspot mutations characterized by the APOBEC SBS2 signature, in conjunction with an uncharacterized mutational context (Ap[C>T]). Next, we developed a statistical framework that identified ApoHMs as drivers in coding and non-coding genomic regions of mUCs. Our results and statistical framework were validated in independent cohorts of 23 non-metastatic UCs and 3,744 samples of 17 metastatic cancers, identifying cancer-type-specific drivers. Our study highlights the role of APOBEC in cancer development and may contribute to developing novel targeted therapy options for APOBEC-driven cancers.

Association of PD-L1 expression with driver gene mutations and clinicopathological characteristics in non-small cell lung cancer: A real-world study of 10 441 patients

BACKGROUND

Programmed death ligand-1 (PD-L1) expression is a well-known predictive biomarker of response to immune checkpoint blockade in non-small cell lung cancer (NSCLC). However, there is limited evidence of the relationship between PD-L1 expression, clinicopathological features, and their association with major driver mutations in NSCLC patients in Latin America.

METHODS

This retrospective study included patients from Argentina with advanced NSCLC, and centralized evaluation of PD-L1 expression concurrently with genomic alterations in the driver genes EGFR, ALK, ROS1, BRAF, and/or KRAS G12C in FFPE tissue samples.

RESULTS

A total of 10 441 patients with advanced NSCLC were analyzed. Adenocarcinoma was the most frequent histological subtype (71.1%). PD-L1 expression was categorized as PD-L1 negative (45.1%), PD-L1 positive low-expression 1%-49% (32.3%), and PD-L1 positive high-expression ≥50% (22.6%). Notably, current smokers and males were more likely to have tumors with PD-L1 tumor proportion score (TPS) ≥50% and ≥ 80% expression, respectively (p < 0.001 and p = 0.013). Tumors with non-adenocarcinoma histology had a significantly higher median PD-L1 expression (p < 0.001). Additionally, PD-L1 in distant nodes was more likely ≥50% (OR 1.60 [95% CI: 1.14-2.25, p < 0.01]). In the multivariate analysis, EGFR-positive tumors were more commonly associated with PD-L1 low expression (OR 0.62 [95% CI: 0.51-0.75], p < 0.01), while ALK-positive tumors had a significant risk of being PD-L1 positive (OR 1.81 [95% CI: 1.30-2.52], p < 0.01).

CONCLUSIONS

PD-L1 expression was associated with well-defined clinicopathological and genomic features. These findings provide a comprehensive view of the expression of PD-L1 in patients with advanced NSCLC in a large Latin American cohort.

Genetic Signature of Human Pancreatic Cancer and Personalized Targeting

Pancreatic cancer is a highly lethal disease with a 5-year survival rate of around 11-12%. Surgery, being the treatment of choice, is only possible in 20% of symptomatic patients. The main reason is that when it becomes symptomatic, IT IS the tumor is usually locally advanced and/or has metastasized to distant organs; thus, early diagnosis is infrequent. The lack of specific early symptoms is an important cause of late diagnosis. Unfortunately, diagnostic tumor markers become positive at a late stage, and there is a lack of early-stage markers. Surgical and non-surgical cases are treated with neoadjuvant and/or adjuvant chemotherapy, and the results are usually poor. However, personalized targeted therapy directed against tumor drivers may improve this situation. Until recently, many pancreatic tumor driver genes/proteins were considered untargetable. Chemical and physical characteristics of mutated KRAS are a formidable challenge to overcome. This situation is slowly changing. For the first time, there are candidate drugs that can target the main driver gene of pancreatic cancer: KRAS. Indeed, KRAS inhibition has been clinically achieved in lung cancer and, at the pre-clinical level, in pancreatic cancer as well. This will probably change the very poor outlook for this disease. This paper reviews the genetic characteristics of sporadic and hereditary predisposition to pancreatic cancer and the possibilities of a personalized treatment according to the genetic signature.

Translational Insights in the Landscape of Salivary Gland Cancers: Ready for a New Era?

Salivary gland carcinomas (SGCs) are rare neoplasms, representing less than 10% of all head and neck tumors, but they are extremely heterogeneous from the histological point of view, their clinical behavior, and their genetics. The guidelines regarding their treatment include surgery in most cases, which can also play an important role in oligometastatic disease. Where surgery cannot be used, systemic therapy comes into play. Systemic therapy for many years has been represented by polychemotherapy, but recently, with the affirmation of translational research, it can also count on targeted therapy, at least in some subtypes of SGCs. Interestingly, in some SGC histotypes, predominant mutations have been identified, which in some cases behave as "driver mutations", namely mutations capable of governing the carcinogenesis process. Targeting these driver mutations may be an effective therapeutic strategy. Nonetheless, it is not always possible to have drugs suitable for targeting driver mutations-and targeting driver mutations is not always accompanied by a clinical benefit. In this review, we will analyze the main mutations predominant in the various histotypes of SGCs.

Exploring FGFR3 Mutations in the Male Germline: Implications for Clonal Germline Expansions and Paternal Age-Related Dysplasias

Delayed fatherhood results in a higher risk of inheriting a new germline mutation that might result in a congenital disorder in the offspring. In particular, some FGFR3 mutations increase in frequency with age, but there are still a large number of uncharacterized FGFR3 mutations that could be expanding in the male germline with potentially early- or late-onset effects in the offspring. Here, we used digital polymerase chain reaction to assess the frequency and spatial distribution of 10 different FGFR3 missense substitutions in the sexually mature male germline. Our functional assessment of the receptor signaling of the variants with biophysical methods showed that 9 of these variants resulted in a higher activation of the receptor´s downstream signaling, resulting in 2 different expansion behaviors. Variants that form larger subclonal expansions in a dissected postmortem testis also showed a positive correlation of the substitution frequency with the sperm donor's age, and a high and ligand-independent FGFR3 activation. In contrast, variants that measured high FGFR3 signaling and elevated substitution frequencies independent of the donor's age did not result in measurable subclonal expansions in the testis. This suggests that promiscuous signal activation might also result in an accumulation of mutations before the sexual maturation of the male gonad with clones staying relatively constant in size throughout time. Collectively, these results provide novel insights into our understanding of the mutagenesis of driver mutations and their resulting mosaicism in the male germline with important consequences for the transmission and recurrence of associated disorders.

Adaptation of a mutual exclusivity framework to identify driver mutations within oncogenic pathways

Distinguishing genomic alterations in cancer-associated genes that have functional impact on tumor growth and disease progression from the ones that are passengers and confer no fitness advantage have important clinical implications. Evidence-based methods for nominating drivers are limited by existing knowledge on the oncogenic effects and therapeutic benefits of specific variants from clinical trials or experimental settings. As clinical sequencing becomes a mainstay of patient care, applying computational methods to mine the rapidly growing clinical genomic data holds promise in uncovering functional candidates beyond the existing knowledge base and expanding the patient population that could potentially benefit from genetically targeted therapies. We propose a statistical and computational method (MAGPIE) that builds on a likelihood approach leveraging the mutual exclusivity pattern within an oncogenic pathway for identifying probabilistically both the specific genes within a pathway and the individual mutations within such genes that are truly the drivers. Alterations in a cancer-associated gene are assumed to be a mixture of driver and passenger mutations with the passenger rates modeled in relationship to tumor mutational burden. We use simulations to study the operating characteristics of the method and assess false-positive and false-negative rates in driver nomination. When applied to a large study of primary melanomas, the method accurately identifies the known driver genes within the RTK-RAS pathway and nominates several rare variants as prime candidates for functional validation. A comprehensive evaluation of MAGPIE against existing tools has also been conducted leveraging the Cancer Genome Atlas data.

Exploring the Micro-Mosaic Landscape of FGFR3 Mutations in the Ageing Male Germline and Their Potential Implications in Meiotic Differentiation

Advanced paternal age increases the risk of transmitting de novo germline mutations, particularly missense mutations activating the receptor tyrosine kinase (RTK) signalling pathway, as exemplified by the FGFR3 mutation, which is linked to achondroplasia (ACH). This risk is attributed to the expansion of spermatogonial stem cells carrying the mutation, forming sub-clonal clusters in the ageing testis, thereby increasing the frequency of mutant sperm and the number of affected offspring from older fathers. While prior studies proposed a correlation between sub-clonal cluster expansion in the testis and elevated mutant sperm production in older donors, limited data exist on the universality of this phenomenon. Our study addresses this gap by examining the testis-expansion patterns, as well as the increases in mutations in sperm for two FGFR3 variants-c.1138G>A (p.G380R) and c.1948A>G (p.K650E)-which are associated with ACH or thanatophoric dysplasia (TDII), respectively. Unlike the ACH mutation, which showed sub-clonal expansion events in an aged testis and a significant increase in mutant sperm with the donor's age, as also reported in other studies, the TDII mutation showed focal mutation pockets in the testis but exhibited reduced transmission into sperm and no significant age-related increase. The mechanism behind this divergence remains unclear, suggesting potential pleiotropic effects of aberrant RTK signalling in the male germline, possibly hindering differentiation requiring meiosis. This study provides further insights into the transmission risks of micro-mosaics associated with advanced paternal age in the male germline.

Prediction of cancer driver genes and mutations: the potential of integrative computational frameworks

The vast amount of available sequencing data allows the scientific community to explore different genetic alterations that may drive cancer or favor cancer progression. Software developers have proposed a myriad of predictive tools, allowing researchers and clinicians to compare and prioritize driver genes and mutations and their relative pathogenicity. However, there is little consensus on the computational approach or a golden standard for comparison. Hence, benchmarking the different tools depends highly on the input data, indicating that overfitting is still a massive problem. One of the solutions is to limit the scope and usage of specific tools. However, such limitations force researchers to walk on a tightrope between creating and using high-quality tools for a specific purpose and describing the complex alterations driving cancer. While the knowledge of cancer development increases daily, many bioinformatic pipelines rely on single nucleotide variants or alterations in a vacuum without accounting for cellular compartments, mutational burden or disease progression. Even within bioinformatics and computational cancer biology, the research fields work in silos, risking overlooking potential synergies or breakthroughs. Here, we provide an overview of databases and datasets for building or testing predictive cancer driver tools. Furthermore, we introduce predictive tools for driver genes, driver mutations, and the impact of these based on structural analysis. Additionally, we suggest and recommend directions in the field to avoid silo-research, moving towards integrative frameworks.

Tissue-Predisposition to Cancer Driver Mutations

Driver mutations are considered the cornerstone of cancer initiation. They are defined as mutations that convey a competitive fitness advantage, and hence, their mutation frequency in premalignant tissue is expected to exceed the basal mutation rate. In old terms, that translates to "the survival of the fittest" and implies that a selective process underlies the frequency of cancer driver mutations. In that sense, each tissue is its own niche that creates a molecular selective pressure that may favor the propagation of a mutation or not. At the heart of this stands one of the biggest riddles in cancer biology: the tissue-predisposition to cancer driver mutations. The frequency of cancer driver mutations among tissues is non-uniform: for instance, mutations in APC are particularly frequent in colorectal cancer, and 99% of chronic myeloid leukemia patients harbor the driver BCR-ABL1 fusion mutation, which is rarely found in solid tumors. Here, we provide a mechanistic framework that aims to explain how tissue-specific features, ranging from epigenetic underpinnings to the expression of viral transposable elements, establish a molecular basis for selecting cancer driver mutations in a tissue-specific manner.

Different Mutational Landscapes in Human Papillomavirus-Induced and Human Papillomavirus-Independent Invasive Penile Squamous Cell Cancers

Penile squamous cell carcinomas (SCC) are rare cancers that arise after transforming human papillomavirus (HPV) infections or independent of HPV in the background of chronic dermatoses. Limited knowledge about genetic alterations driving penile carcinogenesis comes from studies of mainly small cohorts of typically mixed etiology. In this comparative genetic study of HPV-induced and HPV-independent invasive penile SCC of 156 patients from a single institution in a low-incidence country, hotspots of 50 cancer-relevant genes were analyzed with targeted next-generation sequencing. Seventy-nine of 156 SCC were classified as HPV induced, and 77 of 156 SCC arose independent of HPV. Only 28 (35%) of 79 HPV-induced penile SCC, but 69 (90%) of 77 HPV-independent SCC carried somatic gene mutations. PIK3CA, FGFR3, and FBXW7 mutations occurred in both groups in similar numbers as seen in other human cancers. In contrast, mutations in TP53 (44/77; 57%), CDKN2A (35/77; 45%), and HRAS (13/77; 17%) genes occurred with one exception of a HIV positive patient exclusively in HPV-independent SCC with a frequent co-occurrence of TP53 and CDKN2A mutations (28/77; 42%). Mutations in multiple genes occurred in 9 (11%) of 79 HPV-induced SCC versus 47 (62%) of 77 HPV-independent SCC (χ2; P < .001). More than one mutation per gene (multi hits) was characteristic for HPV-independent SCC in 14 (18%) of 77 compared with only 3 (4%) of 79 HPV-induced SCC (χ2; P < .001). The total number of mutations in HPV-induced penile SCC (47 mutations) was significantly lower than that in HPV-independent SCC (143 mutations; Welsh test; P < .001). The presence of somatic driver gene mutations did not correlate with the age of patients, histology, or tumor stage of the primary SCC in either etiologic group, suggesting that acquisition of driver gene mutations is an early event after invasion. This large cohort analysis identified characteristic differences in mutational landscapes for the 2 etiologies. While genetic mutations in tumor suppressor genes drive HPV-independent penile carcinogenesis, oncogenic action of E6 and E7 substitute for mutations in HPV-induced SCC. A subgroup of patients with advanced SCC may be candidates for targeted therapy and clinical trials, although the majority of advanced penile SCC remain a therapeutic challenge.

A workflow to study mechanistic indicators for driver gene prediction with Moonlight

Prediction of driver genes (tumor suppressors and oncogenes) is an essential step in understanding cancer development and discovering potential novel treatments. We recently proposed Moonlight as a bioinformatics framework to predict driver genes and analyze them in a system-biology-oriented manner based on -omics integration. Moonlight uses gene expression as a primary data source and combines it with patterns related to cancer hallmarks and regulatory networks to identify oncogenic mediators. Once the oncogenic mediators are identified, it is important to include extra levels of evidence, called mechanistic indicators, to identify driver genes and to link the observed gene expression changes to the underlying alteration that promotes them. Such a mechanistic indicator could be for example a mutation in the regulatory regions for the candidate gene. Here, we developed new functionalities and released Moonlight2 to provide the user with a mutation-based mechanistic indicator as a second layer of evidence. These functionalities analyze mutations in a cancer cohort to classify them into driver and passenger mutations. Those oncogenic mediators with at least one driver mutation are retained as the final set of driver genes. We applied Moonlight2 to the basal-like breast cancer subtype, lung adenocarcinoma and thyroid carcinoma using data from The Cancer Genome Atlas. For example, in basal-like breast cancer, we found four oncogenes (COPZ2, SF3B4, KRTCAP2 and POLR2J) and nine tumor suppressor genes (KIR2DL4, KIF26B, ARL15, ARHGAP25, EMCN, GMFG, TPK1, NR5A2 and TEK) containing a driver mutation in their promoter region, possibly explaining their deregulation. Moonlight2R is available at https://github.com/ELELAB/Moonlight2R.

Driver Mutations of Pancreatic Cancer Affect Ca2+ Signaling and ATP Production

Glandular pancreatic epithelia of the acinar or ductal phenotype may seem terminally differentiated, but they are characterized by remarkable cell plasticity. Stress-induced trans-differentiation of these cells has been implicated in the mechanisms of carcinogenesis. Current consensus links pancreatic ductal adenocarcinoma with onco-transformation of ductal epithelia, but under the presence of driver mutations in Kras and Trp53, also with trans-differentiation of pancreatic acini. However, we do not know when, in the course of cancer progression, physiological functions are lost by mutant acinar cells, nor can we assess their capacity for the production of pancreatic juice components. Here, we investigated whether two mutations-KrasG12D and Trp53R172H-present simultaneously in acinar cells of KPC mice (model of oncogenesis) influence cytosolic Ca2+ signals. Since Ca2+ signals control the cellular handling of digestive hydrolases, any changes that affect intracellular signaling events and cell bioenergetics might have an impact on the physiology of the pancreas. Our results showed that physiological doses of acetylcholine evoked less regular Ca2+ oscillations in KPC acinar cells compared to the control, whereas responses to supramaximal concentrations were markedly reduced. Menadione elicited Ca2+ signals of different frequencies in KPC cells compared to control cells. Finally, Ca2+ extrusion rates were significantly inhibited in KPC cells, likely due to the lower basal respiration and ATP production. Cumulatively, these findings suggest that driver mutations affect the signaling capacity of pancreatic acinar cells even before the changes in the epithelial cell morphology become apparent.

Cellular and Genetic Background of Osteosarcoma

Osteosarcoma describes a tumor of mesenchymal origin with an annual incidence rate of four to five people per million. Even though chemotherapy treatment has shown success in non-metastatic osteosarcoma, metastatic disease still has a low survival rate of 20%. A targeted therapy approach is limited due to high heterogeneity of tumors, and different underlying mutations. In this review, we will summarize new advances obtained by new technologies, such as next generation sequencing and single-cell sequencing. These new techniques have enabled better assessment of cell populations within osteosarcoma, as well as an understanding of the molecular pathogenesis. We also discuss the presence and properties of osteosarcoma stem cells-the cell population within the tumor that is responsible for metastasis, recurrence, and drug resistance.

Detection of multiple types of cancer driver mutations using targeted RNA sequencing in nonsmall cell lung cancer

BACKGROUND

DNA-based next-generation sequencing has been widely used in the selection of target therapies for patients with nonsmall cell lung cancer (NSCLC). RNA-based next-generation sequencing has been proven to be valuable in detecting fusion and exon-skipping mutations and is recommended by National Comprehensive Cancer Network guidelines for these mutation types.

METHODS

The authors developed an RNA-based hybridization panel targeting actionable driver oncogenes in solid tumors. Experimental and bioinformatics pipelines were optimized for the detection of fusions, single-nucleotide variants (SNVs), and insertion/deletion (indels). In total, 1253 formalin-fixed, paraffin-embedded samples from patients with NSCLC were analyzed by DNA and RNA panel sequencing in parallel to assess the performance of the RNA panel in detecting multiple types of mutations.

RESULTS

In analytical validation, the RNA panel achieved a limit of detection of 1.45-3.15 copies per nanogram for SNVs and 0.21-6.48 copies per nanogram for fusions. In 1253 formalin-fixed, paraffin-embedded NSCLC samples, the RNA panel identified a total of 124 fusion events and 26 MET exon 14-skipping events, in which 14 fusions and six MET exon 14-skipping mutations were missed by DNA panel sequencing. By using the DNA panel as the reference, the positive percent agreement and the positive predictive value of the RNA panel were 98.08% and 98.62%, respectively, for detecting targetable SNVs and 98.15% and 99.38%, respectively, for detecting targetable indels.

CONCLUSIONS

Parallel DNA and RNA sequencing analyses demonstrated the accuracy and robustness of the RNA sequencing panel in detecting multiple types of clinically actionable mutations. The simplified experimental workflow and low sample consumption will make RNA panel sequencing a potentially effective method in clinical testing.

Targeted therapy for lung cancer: Beyond EGFR and ALK

Precision oncology comprises the set of strategies that aim to design the best cancer treatment based on tumor biology. A recognized subset of patients with non-small cell lung cancer (NSCLC) harbor actionable genomic aberrations that can benefit from targeted therapy. In lung cancer, epidermal growth factor receptor (EGFR) mutations and anaplastic lymphoma kinase (ALK) rearrangements are well characterized oncogenic drivers for which the therapeutic use of tyrosine kinase inhibitors has demonstrated improved outcomes compared with chemotherapy. Other druggable targets are also well characterized, and effective inhibitors have been developed and commercialized, leading to a paradigm shift in NSCLC treatment. Here, the authors provide a review of the oncogenic role of the most relevant molecular alterations in NSCLC and emerging treatments in this setting beyond EGFR-driven and ALK-driven diseases.

Cancer driver mutations: predictions and reality

Cancer cells accumulate many genetic alterations throughout their lifetime, but only a few of them drive cancer progression, termed driver mutations. Driver mutations may vary between cancer types and patients, can remain latent for a long time and become drivers at particular cancer stages, or may drive oncogenesis only in conjunction with other mutations. The high mutational, biochemical, and histological tumor heterogeneity makes driver mutation identification very challenging. In this review we summarize recent efforts to identify driver mutations in cancer and annotate their effects. We underline the success of computational methods to predict driver mutations in finding novel cancer biomarkers, including in circulating tumor DNA (ctDNA). We also report on the boundaries of their applicability in clinical research.

Unified views on variant impact across many diseases

Genomic studies of human disorders are often performed by distinct research communities (i.e., focused on rare diseases, common diseases, or cancer). Despite underlying differences in the mechanistic origin of different disease categories, these studies share the goal of identifying causal genomic events that are critical for the clinical manifestation of the disease phenotype. Moreover, these studies face common challenges, including understanding the complex genetic architecture of the disease, deciphering the impact of variants on multiple scales, and interpreting noncoding mutations. Here, we highlight these challenges in depth and argue that properly addressing them will require a more unified vocabulary and approach across disease communities. Toward this goal, we present a unified perspective on relating variant impact to various genomic disorders.

Treatment of advanced non-small cell lung cancer with driver mutations: current applications and future directions

With the improved understanding of driver mutations in non-small cell lung cancer (NSCLC), expanding the targeted therapeutic options improved the survival and safety. However, responses to these agents are commonly temporary and incomplete. Moreover, even patients with the same oncogenic driver gene can respond diversely to the same agent. Furthermore, the therapeutic role of immune-checkpoint inhibitors (ICIs) in oncogene-driven NSCLC remains unclear. Therefore, this review aimed to classify the management of NSCLC with driver mutations based on the gene subtype, concomitant mutation, and dynamic alternation. Then, we provide an overview of the resistant mechanism of target therapy occurring in targeted alternations ("target-dependent resistance") and in the parallel and downstream pathways ("target-independent resistance"). Thirdly, we discuss the effectiveness of ICIs for NSCLC with driver mutations and the combined therapeutic approaches that might reverse the immunosuppressive tumor immune microenvironment. Finally, we listed the emerging treatment strategies for the new oncogenic alternations, and proposed the perspective of NSCLC with driver mutations. This review will guide clinicians to design tailored treatments for NSCLC with driver mutations.

Genetics and RNA Regulation of Uveal Melanoma

Uveal melanoma (UM) is the most common intraocular malignant tumor and the most frequent melanoma not affecting the skin. While the rate of UM occurrence is relatively low, about 50% of patients develop metastasis, primarily to the liver, with lethal outcome despite medical treatment. Notwithstanding that UM etiopathogenesis is still under investigation, a set of known mutations and chromosomal aberrations are associated with its pathogenesis and have a relevant prognostic value. The most frequently mutated genes are BAP1, EIF1AX, GNA11, GNAQ, and SF3B1, with mutually exclusive mutations occurring in GNAQ and GNA11, and almost mutually exclusive ones in BAP1 and SF3B1, and BAP1 and EIF1AX. Among chromosomal aberrations, monosomy of chromosome 3 is the most frequent, followed by gain of chromosome 8q, and full or partial loss of chromosomes 1 and 6. In addition, epigenetic mechanisms regulated by non-coding RNAs (ncRNA), namely microRNAs and long non-coding RNAs, have also been investigated. Several papers investigating the role of ncRNAs in UM have reported that their dysregulated expression affects cancer-related processes in both in vitro and in vivo models. This review will summarize current findings about genetic mutations, chromosomal aberrations, and ncRNA dysregulation establishing UM biology.

An evolution-based machine learning to identify cancer type-specific driver mutations

Identifying cancer type-specific driver mutations is crucial for illuminating distinct pathologic mechanisms across various tumors and providing opportunities of patient-specific treatment. However, although many computational methods were developed to predict driver mutations in a type-specific manner, the methods still have room to improve. Here, we devise a novel feature based on sequence co-evolution analysis to identify cancer type-specific driver mutations and construct a machine learning (ML) model with state-of-the-art performance. Specifically, relying on 28 000 tumor samples across 66 cancer types, our ML framework outperformed current leading methods of detecting cancer driver mutations. Interestingly, the cancer mutations identified by sequence co-evolution feature are frequently observed in interfaces mediating tissue-specific protein-protein interactions that are known to associate with shaping tissue-specific oncogenesis. Moreover, we provide pre-calculated potential oncogenicity on available human proteins with prediction scores of all possible residue alterations through user-friendly website (http://sbi.postech.ac.kr/w/cancerCE). This work will facilitate the identification of cancer type-specific driver mutations in newly sequenced tumor samples.

Brain metastasis screening in the molecular age

The incidence of brain metastases (BM) amongst cancer patients has been increasing due to improvements in therapeutic options and an increase in overall survival. Molecular characterization of tumors has provided insights into the biology and oncogenic drivers of BM and molecular subtype-based screening. Though there are currently some screening and surveillance guidelines for BM, they remain limited. In this comprehensive review, we review and present epidemiological data on BM, their molecular characterization, and current screening guidelines. The molecular subtypes with the highest BM incidence are epithelial growth factor receptor-mutated non-small cell lung cancer (NSCLC), BRCA1, triple-negative (TN), and HER2+ breast cancers, and BRAF-mutated melanoma. Furthermore, BMs are more likely to present asymptomatically at diagnosis in oncogene-addicted NSCLC and BRAF-mutated melanoma. European screening standards recommend more frequent screening for oncogene-addicted NSCLC patients, and clinical trials are investigating screening for BM in hormone receptor+, HER2+, and TN breast cancers. However, more work is needed to determine optimal screening guidelines for other primary cancer molecular subtypes. With the advent of personalized medicine, molecular characterization of tumors has revolutionized the landscape of cancer treatment and prognostication. Incorporating molecular characterization into BM screening guidelines may allow physicians to better identify patients at high risk for BM development and improve patient outcomes.

Impact of Molecular Biology in Diagnosis, Prognosis, and Therapeutic Management of BCR::ABL1-Negative Myeloproliferative Neoplasm

BCR::ABL1-negative myeloproliferative neoplasms (MPNs) include three major subgroups-polycythemia vera (PV), essential thrombocythemia (ET), and primary myelofibrosis (PMF)-which are characterized by aberrant hematopoietic proliferation with an increased risk of leukemic transformation. Besides the driver mutations, which are JAK2, CALR, and MPL, more than twenty additional mutations have been identified through the use of next-generation sequencing (NGS), which can be involved with pathways that regulate epigenetic modifications, RNA splicing, or DNA repair. The aim of this short review is to highlight the impact of molecular biology on the diagnosis, prognosis, and therapeutic management of patients with PV, ET, and PMF.

Disparate Time-to-Treatment and Varied Incidence of Actionable Non-Small Cell Lung Cancer Molecular Alterations in British Columbia: A Historical Cohort Study

Background: non-small cell lung cancer (NSCLC) outcomes remain suboptimal for early-stage disease despite emerging advances in systemic therapy for the peri-operative period. Next-generation sequencing (NGS) identifies driver mutations for which targeted therapies have been developed that improve survival. The BC lung cancer screening program, which was initiated in May 2022, is expected to identify people with early and late stages of NSCLC. It is crucial to first understand the molecular epidemiology and patterns of time to initiate treatment across its five health authorities (HA) to optimize the delivery of care for NSCLC in BC. In this way, we may harness the benefits of targeted therapy for more people with NSCLC as novel advances in therapy continue to emerge. Objective: to compare (a) the frequency of actionable NSCLC molecular alterations among HAs and (b) the time to treatment initiation. Methods: a retrospective observational study was conducted with prospectively collected data from the BC CGL Database. Adults with late stage NSCLC who underwent targeted NGS were included for the time period from May 2020 to June 2021. Demographics, actionable molecular alterations, PDL-1 expression, and time to treatment across HAs were examined. Using appropriate statistical tests for comparison among HAs, p>0.05 was deemed significant. Results: 582 patients underwent NGS/IHC and analysis during the study period. The mean age was 71 (10.1), and 326 (56%) patients were female. A significantly higher proportion of all EGFRm+ were identified within Vancouver Coastal Health (VCHA) and Fraser Health Authority (FHA) compared to the other health authorities (p < 0.001). This also holds true for common sensitizing EGFRm+ alone (p < 0.001) and for sensitizing EGFRm+ when adjusted for females and smoker status (OR 0.75; 95% CI 0.62, 0.92; p = 0.005). Patients residing within the Northern, Interior, and Island HAs were less likely to receive treatment at the same rate as those in VCHA and FHA HAs. Conclusion: actionable NSCLC driver mutations are present in all regional HAs, with disparity noted in time to initiate treatment between HAs. This provides evidence for the importance of molecular testing for patients in all BC HAs to guide personalized and timely NSCLC treatment.

Characterization of driver mutations in Chinese non-small cell lung cancer patients using a novel targeted sequencing panel

Background

The identification of driver mutations has greatly promoted the precise diagnosis and treatment of non-small cell lung cancer (NSCLC), but there is lack of targeted sequencing panels specifically designed and applied to Chinese NSCLC patients. This study aimed to design and validate of a novel sequencing panel for comprehensive characterization of driver mutations in Chinese NSCLC patients, facilitating further exploration of downstream pathway alterations and therapeutic utility.

Methods

A novel target sequencing panel including 21 driver genes was designed and examined in a cohort of 260 Chinese NSCLC patients who underwent surgery in Peking Union Medical College Hospital (PUMCH). Genetic alterations were identified and further analyzed for driver mutations, downstream pathways and therapeutic utilities.

Results

The most frequently identified driver mutations in PUMCH NSCLC cohort were on genes TP53 (28%), EGFR (27%) and PIK3CA (19%) for lung adenocarcinoma (LUAD), and TP53 (41%), PIK3CA (14%) and CDKN2A (13%) for lung squamous cell carcinoma (LUSC), respectively. Downstream pathway analysis revealed common pathways like G1_AND_S1_PHASES pathway were shared not only between LUAD and LUSC patients, but also among three different NSCLC cohorts, while other pathways were subtype-specific, like the unique enrichment of SHC1_EVENT_IN_EGFR_SIGNALING pathway in LUAD patients, and P38_ALPHA_BETA_DOWNSTREAM pathway in LUSC patients, respectively. About 60% of both LUAD and LUSC patients harbored driver mutations as sensitive biomarkers for different targeted therapies, covering not only frequent mutations like EGFR L858R mutation, but also rare mutations like BRAF D594N mutation.

Conclusions

Our study provides a novel target sequencing panel suitable for Chinese NSCLC patients, which can effectively identify driver mutations, analyze downstream pathway alterations and predict therapeutic utility. Overall it is promising to further optimize and apply this panel in clinic with convenience and effectiveness.

MET Signaling Pathways, Resistance Mechanisms, and Opportunities for Target Therapies

The MET gene, known as MET proto-oncogene receptor tyrosine kinase, was first identified to induce tumor cell migration, invasion, and proliferation/survival through canonical RAS-CDC42-PAK-Rho kinase, RAS-MAPK, PI3K-AKT-mTOR, and β-catenin signaling pathways, and its driver mutations, such as MET gene amplification (METamp) and the exon 14 skipping alterations (METex14), activate cell transformation, cancer progression, and worse patient prognosis, principally in lung cancer through the overactivation of their own oncogenic and MET parallel signaling pathways. Because of this, MET driver alterations have become of interest in lung adenocarcinomas since the FDA approval of target therapies for METamp and METex14 in 2020. However, after using MET target therapies, tumor cells develop adaptative changes, favoring tumor resistance to drugs, the main current challenge to precision medicine. Here, we review a link between the resistance mechanism and MET signaling pathways, which is not only limited to MET. The resistance impacts MET parallel tyrosine kinase receptors and signals shared hubs. Therefore, this information could be relevant in the patient's mutational profile evaluation before the first target therapy prescription and follow-up to reduce the risk of drug resistance. However, to develop a resistance mechanism to a MET inhibitor, patients must have access to the drugs. For instance, none of the FDA approved MET inhibitors are registered as such in Chile and other developing countries. Constant cross-feeding between basic and clinical research will thus be required to meet future challenges imposed by the acquired resistance to targeted therapies.

Prognostic Value of Circulating Tumor DNA (ctDNA) in Oncogene-Driven NSCLC: Current Knowledge and Future Perspectives

Simple Summary

Personalized medicine has significantly changed the clinical outcome of oncogene-driven non-small cell lung cancer (NSCLC) due to the efficacy of molecular targeted therapies. Despite the advances in the management of this group of patients, the need for powerful biomarkers with the potential for a real-time assessment of the tumor genomic profile as well as for detecting and monitoring minimal residual disease (MRD) remains unmet. The aim of this article is to present the current knowledge and the future perspectives regarding the prognostic value of ctDNA in NSCLC, focusing on the most common druggable driver mutations, including those in epidermal growth factor receptor (EGFR), anaplastic lymphoma kinase (ALK), c-ros oncogene 1 (ROS1), rearranged during transfection (RET), kirsten rat sarcoma virus (KRAS), B-Raf proto-oncogene (BRAF), and mesenchymal epithelial transition factor receptor (MET) genes.

Abstract

As we enter an unprecedented era of personalized medicine, molecular targeted therapies have the potential to induce improved survival outcome in patients with non-small cell lung cancer (NSCLC). However, a significant percentage of oncogene-driven NSCLC patients will relapse even after definitive treatment, whereas chronic and durable response to targeted therapies is a less common event in advanced-stage lung cancer. This phenomenon could be attributed to minimal residual disease (MRD), defined as a population of disseminated tumor cells that survive during the course or after treatment, eventually leading to recurrence and limiting patient survival. Circulating tumor DNA (ctDNA) is a powerful biomarker for MRD detection and monitoring and is a non-invasive approach of treating cancer, and especially NSCLC, based on a real-time assessment of the tumor genomic landscape. In this review, we present the key findings of studies that have used ctDNA with regard to its prognostic value and in respect to the most common druggable driver mutations of genes in NSCLC, such as epidermal growth factor receptor (EGFR), anaplastic lymphoma kinase (ALK), c-ros oncogene 1 (ROS1), rearranged during transfection (RET), Kirsten rat sarcoma virus (KRAS), B-Raf proto-oncogene (BRAF), and mesenchymal epithelial transition factor receptor (MET).

Hematological relevance of JAK2 V617F and calreticulin mutations in Tunisian patients with essential thrombocythemia

Background

The genetic investigation of essential thrombocythemia(ET) has highlighted the presence of driver mutations in ET. Janus kinase JAK2V617F and calreticulin(CALR) mutations are the most frequent driver mutations and have significantly improved the molecular diagnosis of ET. The impact of genetic heterogeneity on clinical features has not been fully elucidated.

This is the first study which aimed to determine the frequency of JAK2V617F and CALR exon9 mutations in Tunisian ET patients and to establish the correlation between hematological characteristics and mutational status.

Methods

This study included Tunisian patients suspected with ET and was conducted between September 2017 and March 2021. Genomic DNA of patients was isolated from peripheral blood samples. JAK2V617F was detected by AS‐PCR and CALR mutations were detected by PCR/direct sequencing. Clinical and hematological characteristics were also analyzed.

Results

Two hundred and fifty ET patients were enrolled in this study. JAK2V617F mutation was found in 166/250 (66.4%) of patients, whereas CALR mutations were detected in 27/84 (32.1%) patients without JAK2V617F. Compared with JAK2V617F‐positive patients, those with CALR mutations showed lower hemoglobin level and lower leucocytes count (p = 0.007 and p = 0.004,respectively). CALR type 2 was the most frequent mutation of CALR detected in 55.55% of CALR mutated. Six of seven patients with thrombotic events harbored JAK2V617F mutation.

Conclusion

The prevalence of driver mutations JAK2V617F or CALR mutations was 77.2% in Tunisian ET patients. Moreover, patients with JAK2 V617F mutation had a higher risk of thrombosis. The mutational status is necessary to improve the diagnosis and contribute to the therapeutic decisions.

Inflammatory leiomyosarcoma/rhabdomyoblastic tumor: a report of two cases with novel genetic findings

Inflammatory leiomyosarcoma (ILMS) is a malignant neoplasm showing smooth muscle differentiation, a prominent inflammatory infiltrate, and near‐haploidization. These tumors have significant pathologic and genetic overlap with the recently described “inflammatory rhabdomyoblastic tumor (IRT),” suggesting that ILMS and IRT may belong to one entity. Herein, we describe two cases of ILMS/IRT with attention to new cytogenetic and sequencing findings. The tumors were composed of sheets and fascicles of variably pleomorphic tumor cells showing spindled and epithelioid to rhabdoid morphology and a prominent histiocyte‐rich inflammatory infiltrate typical of ILMS/IRT. In case 1, chromosomal microarray analysis showed a near‐haploid pattern with loss of heterozygosity resulting from loss of one copy of all autosomes except for chromosomes 5, 20, 21, and 22. Case 2 showed areas with high‐grade rhabdomyosarcomatous transformation. In this case, the low‐grade tumor component revealed a hyper‐diploid pattern with loss of heterozygosity for most of autosomes but with a normal diploid copy number state except for chromosomes 5, 20, and 22, which showed a relative gain. The high‐grade tumor component showed a similar pattern of copy‐neutral loss of heterozygosity with additional abnormalities, including mosaic segmental gains at 1p, 5p, 8q, 9p, 20q, and segmental loss at 8p. Next‐generation sequencing identified sequence variants in NF1, TP53, SMARCA4, KRAS, and MSH6. MSH6 variant was confirmed as germline, consistent with the diagnosis of hereditary nonpolyposis colorectal cancer (HNPCC) syndrome in one of our study patients and suggestive that ILMS/IRT might be part of the HNPCC cancer spectrum.

Systematic discovery of mutation-directed neo-protein-protein interactions in cancer

Comprehensive sequencing of patient tumors reveals genomic mutations across tumor types that enable tumorigenesis and progression. A subset of oncogenic driver mutations results in neomorphic activity where the mutant protein mediates functions not engaged by the parental molecule. Here, we identify prevalent variant-enabled neomorph-protein-protein interactions (neoPPI) with a quantitative high-throughput differential screening (qHT-dS) platform. The coupling of highly sensitive BRET biosensors with miniaturized coexpression in an ultra-HTS format allows large-scale monitoring of the interactions of wild-type and mutant variant counterparts with a library of cancer-associated proteins in live cells. The screening of 17,792 interactions with 2,172,864 data points revealed a landscape of gain of interactions encompassing both oncogenic and tumor suppressor mutations. For example, the recurrent BRAF V600E lesion mediates KEAP1 neoPPI, rewiring a BRAF^V600E/KEAP1 signaling axis and creating collateral vulnerability to NQO1 substrates, offering a combination therapeutic strategy. Thus, cancer genomic alterations can create neo-interactions, informing variant-directed therapeutic approaches for precision medicine.

Individualized discovery of rare cancer drivers in global network context

Late advances in genome sequencing expanded the space of known cancer driver genes several-fold. However, most of this surge was based on computational analysis of somatic mutation frequencies and/or their impact on the protein function. On the contrary, experimental research necessarily accounted for functional context of mutations interacting with other genes and conferring cancer phenotypes. Eventually, just such results become ‘hard currency’ of cancer biology. The new method, NEAdriver employs knowledge accumulated thus far in the form of global interaction network and functionally annotated pathways in order to recover known and predict novel driver genes. The driver discovery was individualized by accounting for mutations’ co-occurrence in each tumour genome – as an alternative to summarizing information over the whole cancer patient cohorts. For each somatic genome change, probabilistic estimates from two lanes of network analysis were combined into joint likelihoods of being a driver. Thus, ability to detect previously unnoticed candidate driver events emerged from combining individual genomic context with network perspective. The procedure was applied to 10 largest cancer cohorts followed by evaluating error rates against previous cancer gene sets. The discovered driver combinations were shown to be informative on cancer outcome. This revealed driver genes with individually sparse mutation patterns that would not be detectable by other computational methods and related to cancer biology domains poorly covered by previous analyses. In particular, recurrent mutations of collagen, laminin, and integrin genes were observed in the adenocarcinoma and glioblastoma cancers. Considering constellation patterns of candidate drivers in individual cancer genomes opens a novel avenue for personalized cancer medicine.

Machine learning methods for prediction of cancer driver genes: a survey paper

Identifying the genes and mutations that drive the emergence of tumors is a critical step to improving our understanding of cancer and identifying new directions for disease diagnosis and treatment. Despite the large volume of genomics data, the precise detection of driver mutations and their carrying genes, known as cancer driver genes, from the millions of possible somatic mutations remains a challenge. Computational methods play an increasingly important role in discovering genomic patterns associated with cancer drivers and developing predictive models to identify these elements. Machine learning (ML), including deep learning, has been the engine behind many of these efforts and provides excellent opportunities for tackling remaining gaps in the field. Thus, this survey aims to perform a comprehensive analysis of ML-based computational approaches to identify cancer driver mutations and genes, providing an integrated, panoramic view of the broad data and algorithmic landscape within this scientific problem. We discuss how the interactions among data types and ML algorithms have been explored in previous solutions and outline current analytical limitations that deserve further attention from the scientific community. We hope that by helping readers become more familiar with significant developments in the field brought by ML, we may inspire new researchers to address open problems and advance our knowledge towards cancer driver discovery.

Somatic Mosaicism in Biology and Disease

Contrary to earlier beliefs, every cell in the individual is genetically different due to somatic mutations. Consequently, tissues become a mixture of cells with distinct genomes, a phenomenon termed somatic mosaicism. Recent advances in genome sequencing technology have unveiled possible causes of mutations and how they shape the unique mutational landscape of the tissues. Moreover, the analysis of sequencing data in combination with clinical information has revealed the impacts of somatic mosaicism on disease processes. In this review, we discuss somatic mosaicism in various tissues and its clinical implications for human disease.

Clinical and genetic characteristics of early-stage multiple primary and independent primary lung adenocarcinoma patients

AIMS

The difference between multiple primary lung cancers (MPLC) and intrapulmonary metastasis (IM) in patients with lung cancer is vital but controversial. Moreover, the genetic and clinical significance difference between MPLC and independent primary lung cancers (IPLC) patients is unknown.

METHODS

This study retrospectively researched clinical and genetic data of MPLC and IPLC patients from January 2019 to May 2021 at the affiliated hospital of Qingdao University, China. Ninety-four tissue samples from 41 early-stage patients with MPLC, and 94 tissue samples from 94 early-stage patients with IPLC were performed to targeted sequencing.

RESULTS

A total of 36 patients (88%) showed inconsistent driver mutations, and five MPLC patients (12%) shared single identical EGFR/BRAF/TP53 hotspot mutations in the early stage. In MPLC patients, high-frequency mutations included EGFR (63%), TP53 (12%), BRAF (12%), KRAS (10%), ERBB2 (4%), PIK3CA (3%), and MET (3%). In IPLC patients, high-frequency mutations included EGFR (55%), TP53(26%), KRAS (13%), MAP2K1 (5%), PIK3CA (4%), ERBB2 (4%), NF1 (4%), RET (3%), and BRAF (2%). The higher BRAF and fewer TP53 mutations may be related to the lower malignancy in MPLC patients.

CONCLUSIONS

The accuracy of pathological diagnosis in patients with early-stage MPLC does not need comprehensive molecular evaluation to supplement histology for differentiating early-stage MPLC and IM. Meanwhile, the molecular difference between MPLC and IPLC may be helpful to study the mechanism of MPLC pathogenesis.

Oligoprogression in Non-Small Cell Lung Cancer

Simple Summary

Several retrospective studies present evidence of oligoprogressive disease (OPD) in patients with non-small cell lung cancer (NSCLC) with driver mutations such as EGFR. The strategy of local ablative therapy (LAT) with radiotherapy, followed by the continuation of the same anticancer drug therapy beyond progression disease, is recommended in the current NCCN guideline. Although evidence of the use of this strategy in the treatment of the driver mutation-negative NSCLC is missing, LAT with radiotherapy for OPD after combination therapy of immune checkpoint inhibitor with cytotoxic chemotherapy is expected. Tumors outside of the radiation field may further respond to the immune checkpoint inhibitors due to an abscopal effect. In the future, to achieve long-term survival in advanced NSCLC, it will be important to validate this treatment strategy via prospective comparative studies and to actively implement it in clinical practice.

Abstract

We reviewed the literature on oligoprogressive disease (OPD) and local ablative therapy (LAT) in patients with advanced non-small cell lung cancer (NSCLC). The frequency of OPD varies depending on its definition and is estimated to be between 15–47%. The implications of the strategy of continuing the same anticancer agents beyond progressive disease after LAT with radiation therapy for OPD are based on the concept of progression in which only a small number of lesions, not more than about four, proliferate after chemotherapy. In the case of OPD harboring driver mutations such as EGFR, prospective studies are underway. However, evidence from retrospective studies support this strategy, which is currently recommended in some guidelines. The prognosis in OPD cases during the administration of an immune checkpoint inhibitor (ICI) is relatively promising. Additionally, LAT with radiation for OPD after the first-line treatment of ICI with cytotoxic chemotherapy may overcome the resistance to the combination drug therapy due to an abscopal effect. To achieve long-term survival in advanced-stage NSCLC, it is important to verify the optimal method and timing of the therapy through prospective comparative studies as well as patient selection based on patient characteristics and biomarker levels.

Mechanism of activation and the rewired network: New drug design concepts

Precision oncology benefits from effective early phase drug discovery decisions. Recently, drugging inactive protein conformations has shown impressive successes, raising the cardinal questions of which targets can profit and what are the principles of the active/inactive protein pharmacology. Cancer driver mutations have been established to mimic the protein activation mechanism. We suggest that the decision whether to target an inactive (or active) conformation should largely rest on the protein mechanism of activation. We next discuss the recent identification of double (multiple) same-allele driver mutations and their impact on cell proliferation and suggest that like single driver mutations, double drivers also mimic the mechanism of activation. We further suggest that the structural perturbations of double (multiple) in cis mutations may reveal new surfaces/pockets for drug design. Finally, we underscore the preeminent role of the cellular network which is deregulated in cancer. Our structure-based review and outlook updates the traditional Mechanism of Action, informs decisions, and calls attention to the intrinsic activation mechanism of the target protein and the rewired tumor-specific network, ushering innovative considerations in precision medicine.

Profound synchrony of age-specific incidence rates and tumor suppression for different cancer types as revealed by the multistage-senescence model of carcinogenesis

The age-specific trend of cancer incidence rates, but not its magnitude, is well described employing the multistage theory of carcinogenesis by Armitage and Doll in combination with the senescence model of Pompei and Wilson. We derived empirical parameters of the multistage-senescence model from U.S. Surveillance, Epidemiology, and End Results (SEER) incidence data from 2000–2003 and 2010–2013 for The Cancer Genome Atlas (TCGA) cancer types. Under the assumption of a constant tumor-specific transition rate between stages, there is an extremely strong linear relationship (P < 0.0001) between the number of stages and the stage transition rate. The senescence tumor suppression factor for 20 non-reproductive cancers is remarkably consistent (0.0099±0.0005); however, five female reproductive cancers have significantly higher tumor suppression. The peak incidence rate for non-reproductive cancers occurs at a younger age for cancers with fewer stages and their carcinogenic stages are of longer duration. Driver gene mutations are shown to contribute on average only about a third of the carcinogenic stages of different tumor types. A tumor’s accumulated incidence, calculated using a two-variable (age, stage) model, is strongly associated with intrinsic cancer risk. During both early adulthood and senescence, the pace of tumor suppression appears to be synchronized across most cancer types, suggesting the presence of overlapping evolutionary processes.

The concerted action of oncogenic driver mutations directs global translation in intestinal epithelial cells

Oncogenic transformation of colorectal cancer cells is driven by a set of mutations that cause aberrant signaling of growth factor-receptor pathways. Using organoids, we demonstrate that the most frequent driver mutations in APC, KRAS, SMAD4, and TP53 are enhancers of the global mRNA translational capacity, which is linked to intestinal cell growth in an mTOR-dependent manner.

Insights into Mechanisms of Pheochromocytomas and Paragangliomas Driven by Known or New Genetic Drivers

Simple Summary

Pheochromocytomas and paragangliomas are rare neuroendocrine tumors that are often hereditary. Although research has advanced considerably, significant gaps still persist in understanding risk factors, predicting metastatic potential and treating aggressive tumors. The study of rare mutations can provide new insights into how pheochromocytomas and paragangliomas develop. In this review, we provide examples of such rare events and how they can inform our understanding of the spectrum of mutations that can lead to these tumors and improve our ability to provide a genetic diagnosis.

Abstract

Pheochromocytomas and paragangliomas are rare tumors of neural crest origin. Their remarkable genetic diversity and high heritability have enabled discoveries of bona fide cancer driver genes with an impact on diagnosis and clinical management and have consistently shed light on new paradigms in cancer. In this review, we explore unique mechanisms of pheochromocytoma and paraganglioma initiation and management by drawing from recent examples involving rare mutations of hypoxia-related genes VHL, EPAS1 and SDHB, and of a poorly known susceptibility gene, TMEM127. These models expand our ability to predict variant pathogenicity, inform new functional domains, recognize environmental-gene connections, and highlight persistent therapeutic challenges for tumors with aggressive behavior.

Computational studies of anaplastic lymphoma kinase mutations reveal common mechanisms of oncogenic activation

High-risk tumors are genomically heterogeneous, harboring gene amplifications and mutations. The activation status of mutated proteins in cancer can profoundly impact disease progression, patient response, and drug sensitivity. Yet, outside of a few hotspot mutations, functional studies of clinically observed mutations are not commonly pursued. We report a combined experimental profiling and computational analysis of the effects of clinically observed and “test” mutations in the kinase domain of anaplastic lymphoma kinase (ALK), a known oncogenic driver in pediatric neuroblastoma. We find that the activation status of the mutated protein is a good indicator of the transforming ability in NIH 3T3 cells. We also report biophysical as well as data-driven models with predictive power to profile these mutant kinases in silico.

Kinases play important roles in diverse cellular processes, including signaling, differentiation, proliferation, and metabolism. They are frequently mutated in cancer and are the targets of a large number of specific inhibitors. Surveys of cancer genome atlases reveal that kinase domains, which consist of 300 amino acids, can harbor numerous (150 to 200) single-point mutations across different patients in the same disease. This preponderance of mutations—some activating, some silent—in a known target protein make clinical decisions for enrolling patients in drug trials challenging since the relevance of the target and its drug sensitivity often depend on the mutational status in a given patient. We show through computational studies using molecular dynamics (MD) as well as enhanced sampling simulations that the experimentally determined activation status of a mutated kinase can be predicted effectively by identifying a hydrogen bonding fingerprint in the activation loop and the αC-helix regions, despite the fact that mutations in cancer patients occur throughout the kinase domain. In our study, we find that the predictive power of MD is superior to a purely data-driven machine learning model involving biochemical features that we implemented, even though MD utilized far fewer features (in fact, just one) in an unsupervised setting. Moreover, the MD results provide key insights into convergent mechanisms of activation, primarily involving differential stabilization of a hydrogen bond network that engages residues of the activation loop and αC-helix in the active-like conformation (in >70% of the mutations studied, regardless of the location of the mutation).

A systematic view of computational methods for identifying driver genes based on somatic mutation data

Abnormal changes of driver genes are serious for human health and biomedical research. Identifying driver genes, exactly from enormous genes with mutations, promotes accurate diagnosis and treatment of cancer. A lot of works about uncovering driver genes have been developed over the past decades. By analyzing previous works, we find that computational methods are more efficient than traditional biological experiments when distinguishing driver genes from massive data. In this study, we summarize eight common computational algorithms only using somatic mutation data. We first group these methods into three categories according to mutation features they apply. Then, we conclude a general process of nominating candidate cancer driver genes. Finally, we evaluate three representative methods on 10 kinds of cancer derived from The Cancer Genome Atlas Program and five Chinese projects from the International Cancer Genome Consortium. In addition, we compare results of methods with various parameters. Evaluation is performed from four perspectives, including CGC, OG/TSG, Q-value and QQQuantile-Quantileplot. To sum up, we present algorithms using somatic mutation data in order to offer a systematic view of various mutation features and lay the foundation of methods based on integration of mutation information and other types of data.

Clinical Effect of Driver Mutations of KRAS, CDKN2A/P16, TP53, and SMAD4 in Pancreatic Cancer: A Meta-Analysis

Objective: To evaluate the prognostic value of driver mutations in the KRAS, CDKN2A/P16, TP53, and SMAD4 genes in pancreatic cancer to aid in the design of therapeutic strategies. Search Strategy: A systematic search was conducted using PubMed, MEDLINE, Springer, and Cochrane library to identify eligible studies published between January 1990 and June 2018 that reported an association between driver mutations in these genes and survival data. Inclusion Criteria: Articles which passed the primary screen were further scrutinized for the presence of all the following items: (1) cohort studies or case-control studies, evaluating the relationship between driver mutations and cancer; (2) cancer diagnoses clearly proved; and (3) hazard ratios (HR) and 95% confidence intervals (CIs) were characterized by sufficient information. Data Extraction and Analysis: Selection of included articles, data extraction, and methodological quality assessments were, respectively, conducted by two authors. Results: The meta-analysis was composed of 17 studies on the P53, 8 on SMAD4, 7 on CDKN2A/P16, and 2 on KRAS, containing 3373 samples. Our pooled results demonstrated that the patients with overexpression of the P53 (HR = 1.249, 95% CI = 1.003-1.554, p = 0.047), SMAD4 (HR = 1.397, 95% CI = 1.015-1.922, p = 0.040), CDKN2A/P16 (HR = 0.916, 95% CI = 0.583-1.439, p = 0.704), and KRAS (HR = 1.68, 95% CI = 1.27-2.22, p < 0.001) mutations all had poorer overall survival. Conclusion: This systematic review and meta-analysis supports the use of driver mutations in the P53, SMAD4, and KRAS genes as prognostic markers for pancreatic cancer.

The Human Melanoma Proteome Atlas-Complementing the melanoma transcriptome

The MM500 meta-study aims to establish a knowledge basis of the tumor proteome to serve as a complement to genome and transcriptome studies. Somatic mutations and their effect on the transcriptome have been extensively characterized in melanoma. However, the effects of these genetic changes on the proteomic landscape and the impact on cellular processes in melanoma remain poorly understood. In this study, the quantitative mass-spectrometry-based proteomic analysis is interfaced with pathological tumor characterization, and associated with clinical data. The melanoma proteome landscape, obtained by the analysis of 505 well-annotated melanoma tumor samples, is defined based on almost 16 000 proteins, including mutated proteoforms of driver genes. More than 50 million MS/MS spectra were analyzed, resulting in approximately 13,6 million peptide spectrum matches (PSMs). Altogether 13 176 protein-coding genes, represented by 366 172 peptides, in addition to 52 000 phosphorylation sites, and 4 400 acetylation sites were successfully annotated. This data covers 65% and 74% of the predicted and identified human proteome, respectively. A high degree of correlation (Pearson, up to 0.54) with the melanoma transcriptome of the TCGA repository, with an overlap of 12 751 gene products, was found. Mapping of the expressed proteins with quantitation, spatiotemporal localization, mutations, splice isoforms, and PTM variants was proven not to be predicted by genome sequencing alone. The melanoma tumor molecular map was complemented by analysis of blood protein expression, including data on proteins regulated after immunotherapy. By adding these key proteomic pillars, the MM500 study expands the knowledge on melanoma disease.

Predictive testing in non-small cell lung carcinoma

BACKGROUND

Predictive testing is a crucial part of the complete diagnostic process of non-small cell lung cancer (NSCLC) and a necessary requirement in order to determine proper course of treatment. However, the possibilities of testing and the spectrum of examined markers are quickly evolving as a result of the progress in diagnostic and therapeutic possibilities, and as such it is necessary to regularly update the current guidelines to achieve proper standards of care in routine practice.

PURPOSE

To provide a complex overview of the current problematics of predictive testing in NSCLC at a molecular level, considering also the evaluation of PD-L1 expression based on the international and national guidelines. To summarize the current state of predictive testing employed in NSCLC in the Czech Republic.

CONCLUSION

Predictive testing in NSCLC is a part of routine diagnostic practice; however, as a result of the expanding spectrum of diagnostic and therapeutic possibilities, it is undergoing significant development. The existing method of the sequential testing of individual markers is becoming unsuitable; given the increasing number of potential predictors and complex molecular testing, the use of new generation sequencing appears to represent a more suitable solution. The immunohistochemical evaluation of PD-L1 expression is also a necessary part of predictive testing in NSCLC.

Current challenges to underpinning the genetic basis for cholangiocarcinoma

AREAS COVERED

This review provides an overview regarding the current scenario and knowledge of the CCA genomic landscape and the potentially actionable molecular aberrations in each CCA subtype.

EXPERT OPINION

The establishment and advances of high-throughput methodologies applied to genetic and epigenetic profiling are changing many cancer types' therapeutic landscape , including CCA.The large body of data generated must be interpreted appropriately and eventually implemented in clinical practice. The following advancements toward precision medicine in CCA management will require designing better clinical trials with improved methods to stratify biliary tumor patients.

Deleterious point mutations in T-cell acute lymphoblastic leukemia: Mechanistic insights into leukemogenesis

T-cell acute lymphoblastic leukemia (T-ALL) is characterized by the leukemogenic transformation of immature T cells, which accumulate an array of genetic and epigenetic lesions, leading to a sustained proliferation of abnormal T cells. Genetic alterations in the DNA repair genes, protooncogenes, transcription factors, and epigenetic modifiers have been studied in the past decade using next-generation sequencing and high-resolution copy number arrays. While other genomic lesions like chromosomal rearrangements, inversions, insertions, and gene fusions have been well studied at functional level, the mechanism of generation of driver mutations in T-ALL is the subject of current investigation. Novel oncogenic mutations in the TP53, BRCA2, PTEN, IL7R, RAS, NOTCH1, ETV6, BCL11B, WT1, DNMT3A, PRC2, PHF6, USP7, KDM6A and an array of other genes disrupt the genetic and epigenetic homeostasis in T-ALL. In this review, we have summarized the mechanistic role of deleterious driver mutations in T-ALL initiation and progression. We speculate that the formation of non-B DNA structures could be one of the primary reasons for the occurrence of different genomic lesions seen in T-ALL, which warrants further investigation. Understanding the mechanism behind the genesis of oncogenic mutations will pave the way to develop targeted therapies that can improve the overall survival and treatment outcome.

Cutaneous Melanoma: Mutational Status and Potential Links to Tertiary Lymphoid Structure Formation

Recent advances in immunotherapy have enabled rapid evolution of novel interventional approaches designed to reinvigorate and expand patient immune responses against cancer. An emerging approach in cancer immunology involves the conditional induction of tertiary lymphoid structures (TLS), which are non-encapsulated ectopic lymphoid structures forming at sites of chronic, pathologic inflammation. Cutaneous melanoma (CM), a highly-immunogenic form of solid cancer, continues to rise in both incidence and mortality rate, with recent reports supporting a positive correlation between the presence of TLS in melanoma and beneficial treatment outcomes amongst advanced-stage patients. In this context, TLS in CM are postulated to serve as dynamic centers for the initiation of robust anti-tumor responses within affected regions of active disease. Given their potential importance to patient outcome, significant effort has been recently devoted to gaining a better understanding of TLS neogenesis and the influence these lymphoid organs exert within the tumor microenvironment. Here, we briefly review TLS structure, function, and response to treatment in the setting of CM. To uncover potential tumor-intrinsic mechanisms that regulate TLS formation, we have taken the novel perspective of evaluating TLS induction in melanomas impacted by common driver mutations in BRAF, PTEN, NRAS, KIT, PRDM1, and MITF. Through analysis of The Cancer Genome Atlas (TCGA), we show expression of DNA repair proteins (DRPs) including BRCA1, PAXIP, ERCC1, ERCC2, ERCC3, MSH2, and PMS2 to be negatively correlated with expression of pro-TLS genes, suggesting DRP loss may favor TLS development in support of improved patient outcome and patient response to interventional immunotherapy.

Tumour-Agnostic Therapy for Pancreatic Cancer and Biliary Tract Cancer

The prognosis of patients with solid tumours has remarkably improved with the development of molecular-targeted drugs and immune checkpoint inhibitors. However, the improvements in the prognosis of pancreatic cancer and biliary tract cancer is delayed compared to other carcinomas, and the 5-year survival rates of distal-stage disease are approximately 10 and 20%, respectively. However, a comprehensive analysis of tumour cells using The Cancer Genome Atlas (TCGA) project has led to the identification of various driver mutations. Evidently, few mutations exist across organs, and basket trials targeting driver mutations regardless of the primary organ are being actively conducted. Such basket trials not only focus on the gate keeper-type oncogene mutations, such as HER2 and BRAF, but also focus on the caretaker-type tumour suppressor genes, such as BRCA1/2, mismatch repair-related genes, which cause hereditary cancer syndrome. As oncogene panel testing is a vital approach in routine practice, clinicians should devise a strategy for improved understanding of the cancer genome. Here, the gene mutation profiles of pancreatic cancer and biliary tract cancer have been outlined and the current status of tumour-agnostic therapy in these cancers has been reported.

PD-L1 Expression in Chinese Patients with Advanced Non-Small Cell Lung Cancer (NSCLC): A Multi-Center Retrospective Observational Study

Objective: This study aimed to investigate the prevalence of tumor programmed death-ligand 1 (PD-L1) expression in Chinese patients with advanced Non-Small Cell Lung Cancer (NSCLC). Methods: Tumor tissues with histologically confirmed stage IIIB/IV NSCLC were retrospectively obtained from 10 centers in China. PD-L1 expression was determined using the PD-L1 IHC 22C3 pharmDx kit (Agilent, Santa Clara, CA, USA) and the samples were repetitively assayed with the PD-L1 IHC 22C3 Ab concentrate (Agilent, Santa Clara, CA, USA). Results: Out of 901 patients who met the inclusion criteria, 879 (97.6%) had evaluable PD-L1 data. The number of patients with a PD-L1 tumor proportion score (TPS) < 1%, 1-49%, and ≥ 50% (corresponding to PD-L1 non-expression, low expression, and high expression) was 424 (48.2%), 266 (30.3%), and 189 (21.5%), respectively. PD-L1 expression was more likely to be found in patients younger than 75 years, men, current or former smokers, those with good performance status (PS) scores, and those with a wild-type epidermal growth factor receptor (EGFR). PD-L1 TPS ≥ 50% and ≥ 1% were respectively 28.0% and 50.2% among patients negative for both EGFR mutation and anaplastic lymphoma kinase (ALK) rearrangement. PD-L1 expression determined using the 22C3 antibody concentrate and pharmDx kit had comparable results. Conclusions: The prevalence of PD‑L1 expression in advanced NSCLC was consistent with that reported in the global EXPRESS study. Age, gender, smoking history, PS scores, and EGFR/ALK mutation status affected PD-L1 expression. The 22C3 antibody concentrate appears to be an alternative reagent for the PD-L1 assay.

Treatment of advanced nonsmall cell lung cancer: First line, maintenance and second line - Indian consensus statement update

The management of advanced nonsmall cell lung cancer (NSCLC) patients is becoming increasingly complex with the identification of driver mutations/rearrangements and development/availability of appropriate targeted therapies. In 2017, an expert group of medical oncologists with expertise in treating lung cancer used data from published literature and experience to arrive at practical consensus recommendations on treatment of advanced NSCLC for use by the community oncologists. This was published subsequently in the Indian Journal of Cancer with a plan to be updated annually. The present document is an update to the 2017 document.