Rectal Cancer after Prostate Radiation: A Complex and Controversial Disease.

A small proportion of rectal adenocarcinomas develop in patients many years after the treatment of a previous cancer using pelvic radiation, and the incidence of these rectal cancers depends on the length of follow-up from the end of radiotherapy. The risk of radiation-associated rectal cancer (RARC) is higher in patients treated with prostate external beam radiotherapy than it is in patients treated with brachytherapy. The molecular features of RARC have not been fully investigated, and survival is lower compared to non-irradiated rectal cancer patients. Ultimately, it is unclear whether the worse outcomes are related to differences in patient characteristics, treatment-related factors, or tumor biology. Radiation is widely used in the management of rectal adenocarcinoma; however, pelvic re-irradiation of RARC is challenging and carries a higher risk of treatment complications. Although RARC can develop in patients treated for a variety of malignancies, it is most common in patients treated for prostate cancer. This study will review the incidence, molecular characteristics, clinical course, and treatment outcomes of rectal adenocarcinoma in patients previously treated with radiation for prostate cancer. For clarity, we will distinguish between rectal cancer not associated with prostate cancer (RCNAPC), rectal cancer in non-irradiated prostate cancer patients (RCNRPC), and rectal cancer in irradiated prostate cancer patients (RCRPC). RARC represents a unique but understudied subset of rectal cancer, and thus requires a more comprehensive investigation in order to improve its treatment and prognosis.

Outcomes and Molecular Features of Brain Metastasis in Gastroesophageal Adenocarcinoma.

Importance: Brain metastasis (BrM) in gastroesophageal adenocarcinoma (GEA) is a rare and poorly understood phenomenon associated with poor prognosis. Objectives: To examine the clinical and genomic features of patients with BrM from GEA and evaluate factors associated with survival. Design, Setting, and Participants: In this single-institution retrospective cohort study, 68 patients with BrM from GEA diagnosed between January 1, 2008, and December 31, 2020, were identified via review of billing codes and imaging reports from the electronic medical record with follow-up through November 3, 2021. Genomic data were derived from the Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets clinical sequencing platform. Exposures: Treatment with BrM resection and/or radiotherapy. Main Outcomes and Measures: Overall survival after BrM diagnosis. Results: Sixty-eight patients (median age at diagnosis, 57.4 years [IQR, 49.8-66.4 years]; 59 [86.8%] male; 55 [85.9%] White) participated in the study. A total of 57 (83.8%) had primary tumors in the distal esophagus or gastroesophageal junction. Median time from initial diagnosis to BrM diagnosis was 16.9 months (IQR, 8.5-27.7 months). Median survival from BrM diagnosis was 8.7 months (95% CI, 5.5-11.5 months). Overall survival was 35% (95% CI, 25%-48%) at 1 year and 24% (95% CI, 16%-37%) at 2 years. In a multivariable analysis, an Eastern Cooperative Oncology Group performance status of 2 or greater (hazard ratio [HR], 4.66; 95% CI, 1.47-14.70; P = .009) and lack of surgical or radiotherapeutic intervention (HR, 7.71; 95% CI, 2.01-29.60; P = .003) were associated with increased risk of all-cause mortality, whereas 3 or more extracranial sites of disease (HR, 1.85; 95% CI, 0.64-5.29; P = .25) and 4 or more BrMs (HR, 2.15; 95% CI, 0.93-4.98; P = .07) were not statistically significant. A total of 31 patients (45.6%) had ERBB2 (formerly HER2 or HER2/neu)-positive tumors, and alterations in ERBB2 were enriched in BrM relative to primary tumors (8 [47.1%] vs 7 [20.6%], P = .05), as were alterations in PTPRT (7 [41.2%] vs 4 [11.8%], P = .03). Conclusions and Relevance: This study suggests that that a notable proportion of patients with BrM from GEA achieve survival exceeding 1 and 2 years from BrM diagnosis, a more favorable prognosis than previously reported. Good performance status and treatment with combination surgery and radiotherapy were associated with the best outcomes. ERBB2 positivity and amplification as well as PTPRT alterations were enriched in BrM tissue compared with primary tumors; therefore, further study should be pursued to identify whether these variables represent genomic risk factors for BrM development.

Genomic and transcriptomic determinants of response to neoadjuvant therapy in rectal cancer.

The incidence of rectal cancer is increasing in patients younger than 50 years. Locally advanced rectal cancer is still treated with neoadjuvant radiation, chemotherapy and surgery, but recent evidence suggests that patients with a complete response can avoid surgery permanently. To define correlates of response to neoadjuvant therapy, we analyzed genomic and transcriptomic profiles of 738 untreated rectal cancers. APC mutations were less frequent in the lower than in the middle and upper rectum, which could explain the more aggressive behavior of distal tumors. No somatic alterations had significant associations with response to neoadjuvant therapy in a treatment-agnostic manner, but KRAS mutations were associated with faster relapse in patients treated with neoadjuvant chemoradiation followed by consolidative chemotherapy. Overexpression of IGF2 and L1CAM was associated with decreased response to neoadjuvant therapy. RNA-sequencing estimates of immune infiltration identified a subset of microsatellite-stable immune hot tumors with increased response and prolonged disease-free survival.

Clinical sequencing of soft tissue and bone sarcomas delineates diverse genomic landscapes and potential therapeutic targets.

The genetic, biologic, and clinical heterogeneity of sarcomas poses a challenge for the identification of therapeutic targets, clinical research, and advancing patient care. Because there are > 100 sarcoma subtypes, in-depth genetic studies have focused on one or a few subtypes. Herein, we report a comparative genetic analysis of 2,138 sarcomas representing 45 pathological entities. This cohort is prospectively analyzed using targeted sequencing to characterize subtype-specific somatic alterations in targetable pathways, rates of whole genome doubling, mutational signatures, and subtype-agnostic genomic clusters. The most common alterations are in cell cycle control and TP53, receptor tyrosine kinases/PI3K/RAS, and epigenetic regulators. Subtype-specific associations include TERT amplification in intimal sarcoma and SWI/SNF alterations in uterine adenosarcoma. Tumor mutational burden, while low compared to other cancers, varies between and within subtypes. This resource will improve sarcoma models, motivate studies of subtype-specific alterations, and inform investigations of genetic factors and their correlations with treatment response.

Genomic characterization of metastatic patterns from prospective clinical sequencing of 25,000 patients.

Metastatic progression is the main cause of death in cancer patients, whereas the underlying genomic mechanisms driving metastasis remain largely unknown. Here, we assembled MSK-MET, a pan-cancer cohort of over 25,000 patients with metastatic diseases. By analyzing genomic and clinical data from this cohort, we identified associations between genomic alterations and patterns of metastatic dissemination across 50 tumor types. We found that chromosomal instability is strongly correlated with metastatic burden in some tumor types, including prostate adenocarcinoma, lung adenocarcinoma, and HR+/HER2+ breast ductal carcinoma, but not in others, including colorectal cancer and high-grade serous ovarian cancer, where copy-number alteration patterns may be established early in tumor development. We also identified somatic alterations associated with metastatic burden and specific target organs. Our data offer a valuable resource for the investigation of the biological basis for metastatic spread and highlight the complex role of chromosomal instability in cancer progression.

Computational methods and translational applications for targeted next-generation sequencing platforms.

During the past decade, next-generation sequencing (NGS) technologies have become widely adopted in cancer research and clinical care. Common applications within the clinical setting include patient stratification into relevant molecular subtypes, identification of biomarkers of response and resistance to targeted and systemic therapies, assessment of heritable cancer risk based on known pathogenic variants, and longitudinal monitoring of treatment response. The need for efficient downstream processing and reliable interpretation of sequencing data has led to the development of novel algorithms and computational pipelines, as well as structured knowledge bases that link genomic alterations to currently available drugs and ongoing clinical trials. Cancer centers around the world use different types of targeted solid-tissue and blood based NGS assays to analyze the genomic and transcriptomic profile of patients as part of their routine clinical care. Recently, cross-institutional collaborations have led to the creation of large pooled datasets that can offer valuable insights into the genomics of rare cancers.

Patterns of Metastatic Disease in Patients with Cancer Derived from Natural Language Processing of Structured CT Radiology Reports over a 10-year Period.

Background Patterns of metastasis in cancer are increasingly relevant to prognostication and treatment planning but have historically been documented by means of autopsy series. Purpose To show the feasibility of using natural language processing (NLP) to gather accurate data from radiology reports for assessing spatial and temporal patterns of metastatic spread in a large patient cohort. Materials and Methods In this retrospective longitudinal study, consecutive patients who underwent CT from July 2009 to April 2019 and whose CT reports followed a departmental structured template were included. Three radiologists manually curated a sample of 2219 reports for the presence or absence of metastases across 13 organs; these manually curated reports were used to develop three NLP models with an 80%-20% split for training and test sets. A separate random sample of 448 manually curated reports was used for validation. Model performance was measured by accuracy, precision, and recall for each organ. The best-performing NLP model was used to generate a final database of metastatic disease across all patients. For each cancer type, statistical descriptive reports were provided by analyzing the frequencies of metastatic disease at the report and patient levels. Results In 91 665 patients (mean age ± standard deviation, 61 years ± 15; 46 939 women), 387 359 reports were labeled. The best-performing NLP model achieved accuracies from 90% to 99% across all organs. Metastases were most frequently reported in abdominopelvic (23.6% of all reports) and thoracic (17.6%) nodes, followed by lungs (14.7%), liver (13.7%), and bones (9.9%). Metastatic disease tropism is distinct among common cancers, with the most common first site being bones in prostate and breast cancers and liver among pancreatic and colorectal cancers. Conclusion Natural language processing may be applied to cancer patients' CT reports to generate a large database of metastatic phenotypes. Such a database could be combined with genomic studies and used to explore prognostic imaging phenotypes with relevance to treatment planning. © RSNA, 2021 Online supplemental material is available for this article.

CRISPR Gene Drive Efficiency and Resistance Rate Is Highly Heritable with No Common Genetic Loci of Large Effect.

Gene drives could allow for control of vector-borne diseases by directly suppressing vector populations or spreading genetic payloads designed to reduce pathogen transmission. Clustered regularly interspaced short palindromic repeat (CRISPR) homing gene drives work by cleaving wild-type alleles, which are then converted to drive alleles by homology-directed repair, increasing the frequency of the drive in a population over time. However, resistance alleles can form when end-joining repair takes place in lieu of homology-directed repair. Such alleles cannot be converted to drive alleles, which would eventually halt the spread of a drive through a population. To investigate the effects of natural genetic variation on resistance formation, we developed a CRISPR homing gene drive in Drosophila melanogaster and crossed it into the genetically diverse Drosophila Genetic Reference Panel (DGRP) lines, measuring several performance parameters. Most strikingly, resistance allele formation postfertilization in the early embryo ranged from 7 to 79% among lines and averaged 42 ± 18%. We performed a genome-wide association study using our results in the DGRP lines, and found that the resistance and conversion rates were not explained by common alleles of large effect, but instead there were several genetic polymorphisms showing weak association. RNA interference knockdown of several genes containing these polymorphisms confirmed their effect, but the small effect sizes imply that their manipulation would likely yield only modest improvements to the efficacy of gene drives.

Maximum Likelihood Estimation of Fitness Components in Experimental Evolution.

Estimating fitness differences between allelic variants is a central goal of experimental evolution. Current methods for inferring such differences from allele frequency time series typically assume that the effects of selection can be described by a fixed selection coefficient. However, fitness is an aggregate of several components including mating success, fecundity, and viability. Distinguishing between these components could be critical in many scenarios. Here, we develop a flexible maximum likelihood framework that can disentangle different components of fitness from genotype frequency data, and estimate them individually in males and females. As a proof-of-principle, we apply our method to experimentally evolved cage populations of Drosophila melanogaster, in which we tracked the relative frequencies of a loss-of-function and wild-type allele of yellow This X-linked gene produces a recessive yellow phenotype when disrupted and is involved in male courtship ability. We find that the fitness costs of the yellow phenotype take the form of substantially reduced mating preference of wild-type females for yellow males, together with a modest reduction in the viability of yellow males and females. Our framework should be generally applicable to situations where it is important to quantify fitness components of specific genetic variants, including quantitative characterization of the population dynamics of CRISPR gene drives.

Reducing resistance allele formation in CRISPR gene drive.

CRISPR homing gene drives can convert heterozygous cells with one copy of the drive allele into homozygotes, thereby enabling super-Mendelian inheritance. Such a mechanism could be used, for example, to rapidly disseminate a genetic payload in a population, promising effective strategies for the control of vector-borne diseases. However, all CRISPR homing gene drives studied in insects thus far have produced significant quantities of resistance alleles that would limit their spread. In this study, we provide an experimental demonstration that multiplexing of guide RNAs can both significantly increase the drive conversion efficiency and reduce germline resistance rates of a CRISPR homing gene drive in Drosophila melanogaster We further show that an autosomal drive can achieve drive conversion in the male germline, with no subsequent formation of resistance alleles in embryos through paternal carryover of Cas9. Finally, we find that the nanos promoter significantly lowers somatic Cas9 expression compared with the vasa promoter, suggesting that nanos provides a superior choice in drive strategies where gene disruption in somatic cells could have fitness costs. Comparison of drive parameters among the different constructs developed in this study and a previous study suggests that, while drive conversion and germline resistance rates are similar between different genomic targets, embryo resistance rates can vary significantly. Taken together, our results mark an important step toward developing effective gene drives capable of functioning in natural populations and provide several possible avenues for further control of resistance rates.