Closing the gap: prognostic and predictive biomarker validation for personalized care in a Latin American hormone-dependent breast cancer cohort.

BACKGROUND: Several guidelines recommend the use of different classifiers to determine the risk of recurrence (ROR) and treatment decisions in patients with HR+HER2- breast cancer. However, data are still lacking for their usefulness in Latin American (LA) patients. Our aim was to evaluate the comparative prognostic and predictive performance of different ROR classifiers in a real-world LA cohort. METHODS: The Molecular Profile of Breast Cancer Study (MPBCS) is an LA case-cohort study with 5-year follow-up. Stages I and II, clinically node-negative HR+HER2- patients (n = 340) who received adjuvant hormone therapy and/or chemotherapy, were analyzed. Time-dependent receiver-operator characteristic-area under the curve, univariate and multivariate Cox proportional hazards regression (CPHR) models were used to compare the prognostic performance of several risk biomarkers. Multivariate CPHR with interaction models tested the predictive ability of selected risk classifiers. RESULTS: Within this cohort, transcriptomic-based classifiers such as the recurrence score (RS), EndoPredict (EP risk and EPClin), and PAM50-risk of recurrence scores (ROR-S and ROR-PC) presented better prognostic performances for node-negative patients (univariate C-index 0.61-0.68, adjusted C-index 0.77-0.80, adjusted hazard ratios [HR] between high and low risk: 4.06-9.97) than the traditional classifiers Ki67 and Nottingham Prognostic Index (univariate C-index 0.53-0.59, adjusted C-index 0.72-0.75, and adjusted HR 1.85-2.54). RS (and to some extent, EndoPredict) also showed predictive capacity for chemotherapy benefit in node-negative patients (interaction P = .0200 and .0510, respectively). CONCLUSION: In summary, we could prove the clinical validity of most transcriptomic-based risk classifiers and their superiority over clinical and immunohistochemical-based methods in the heterogenous, real-world node-negative HR+HER2- MPBCS cohort.

Novel evaluation approach for molecular signature-based deconvolution methods.

The tumoral immune microenvironment (TIME) plays a key role in prognosis, therapeutic approach and pathophysiological understanding over oncological processes. Several computational immune cell-type deconvolution methods (DM), supported by diverse molecular signatures (MS), have been developed to uncover such TIME interplay from RNA-seq tumor biopsies. MS-DM pairs were benchmarked against each other by means of different metrics, such as Pearson's correlation, R2 and RMSE, but these only evaluate the linear association of the estimated proportion related to the expected one, missing the analysis of prediction-dependent bias trends and cell identification accuracy. We present a novel protocol composed of four tests allowing appropriate evaluation of the cell type identification performance and proportion prediction accuracy of molecular signature-deconvolution method pair by means of certainty and confidence cell-type identification scores (F1-score, distance to the optimal point and error rates) as well the Bland-Altman method for error-trend analysis. Our protocol was used to benchmark six state-of-the-art DMs (CIBERSORTx, DCQ, DeconRNASeq, EPIC, MIXTURE and quanTIseq) paired to five murine tissue-specific MSs, revealing a systematic overestimation of the number of different cell types across almost all methods.

Cancer health disparities in racial/ethnic minorities in the United States.

There are well-established disparities in cancer incidence and outcomes by race/ethnicity that result from the interplay between structural, socioeconomic, socio-environmental, behavioural and biological factors. However, large research studies designed to investigate factors contributing to cancer aetiology and progression have mainly focused on populations of European origin. The limitations in clinicopathological and genetic data, as well as the reduced availability of biospecimens from diverse populations, contribute to the knowledge gap and have the potential to widen cancer health disparities. In this review, we summarise reported disparities and associated factors in the United States of America (USA) for the most common cancers (breast, prostate, lung and colon), and for a subset of other cancers that highlight the complexity of disparities (gastric, liver, pancreas and leukaemia). We focus on populations commonly identified and referred to as racial/ethnic minorities in the USA-African Americans/Blacks, American Indians and Alaska Natives, Asians, Native Hawaiians/other Pacific Islanders and Hispanics/Latinos. We conclude that even though substantial progress has been made in understanding the factors underlying cancer health disparities, marked inequities persist. Additional efforts are needed to include participants from diverse populations in the research of cancer aetiology, biology and treatment. Furthermore, to eliminate cancer health disparities, it will be necessary to facilitate access to, and utilisation of, health services to all individuals, and to address structural inequities, including racism, that disproportionally affect racial/ethnic minorities in the USA.

Personalizing Precision Oncology Clinical Trials in Latin America: An Expert Panel on Challenges and Opportunities.

The participation of patients in precision oncology trials needs to fulfill molecular-based selection criteria. This strongly limits accrual, and as a consequence, screening successes have decreased, costs have increased, and fewer subjects are enrolled. To achieve narrowed targets, studies have been forced to be multicenter and multinational to reach a larger pool of candidates. However, this globalization faces many challenges, as, for example, in the case of precision oncology trials. These trials have a complex structure that is dependent upon a high-tech infrastructure and knowledge in a dynamic environment. Given the movement of precision clinical cancer research to regions other than Europe and the U.S., it is important to evaluate the feasibility of performing such trials in lower-middle- and low-income countries. Here we critically discuss the advantages of conducting precision oncology clinical trials in Latin America and make suggestions on how to overcome the main challenges involved. IMPLICATIONS FOR PRACTICE: Precision clinical trials in oncology are studies that require candidates to have tumors with specific molecular alterations, which are considered the target for the trial experimental therapy. Because many molecular alterations are rare, fewer patients are enrolled. This has led to trials being forced to be multicenter and multinational, including trials in Latin America. This article discusses the challenges and opportunities to conduct precision oncology trials in Latin America, aiming to help sponsors and investigators to solve complex issues that ultimately lead to more of such trials being run in the region, potentially benefiting more Latin American patients with cancer.

Massive integrative gene set analysis enables functional characterization of breast cancer subtypes.

The availability of large-scale repositories and integrated cancer genome efforts have created unprecedented opportunities to study and describe cancer biology. In this sense, the aim of translational researchers is the integration of multiple omics data to achieve a better identification of homogeneous subgroups of patients in order to develop adequate diagnostic and treatment strategies from the personalized medicine perspective. So far, existing integrative methods have grouped together omics data information, leaving out individual omics data phenotypic interpretation. Here, we present the Massive and Integrative Gene Set Analysis (MIGSA) R package. This tool can analyze several high throughput experiments in a comprehensive way through a functional analysis strategy, relating a phenotype to its biological function counterpart defined by means of gene sets. By simultaneously querying different multiple omics data from the same or different groups of patients, common and specific functional patterns for each studied phenotype can be obtained. The usefulness of MIGSA was demonstrated by applying the package to functionally characterize the intrinsic breast cancer PAM50 subtypes. For each subtype, specific functional transcriptomic profiles and gene sets enriched by transcriptomic and proteomic data were identified. To achieve this, transcriptomic and proteomic data from 28 datasets were analyzed using MIGSA. As a result, enriched gene sets and important genes were consistently found as related to a specific subtype across experiments or data types and thus can be used as molecular signature biomarkers.

A novel non-parametric method for uncertainty evaluation of correlation-based molecular signatures: its application on PAM50 algorithm.

Motivation: The PAM50 classifier is used to assign patients to the highest correlated breast cancer subtype irrespectively of the obtained value. Nonetheless, all subtype correlations are required to build the risk of recurrence (ROR) score, currently used in therapeutic decisions. Present subtype uncertainty estimations are not accurate, seldom considered or require a population-based approach for this context. Results: Here we present a novel single-subject non-parametric uncertainty estimation based on PAM50's gene label permutations. Simulations results ( n = 5228) showed that only 61% subjects can be reliably 'Assigned' to the PAM50 subtype, whereas 33% should be 'Not Assigned' (NA), leaving the rest to tight 'Ambiguous' correlations between subtypes. The NA subjects exclusion from the analysis improved survival subtype curves discrimination yielding a higher proportion of low and high ROR values. Conversely, all NA subjects showed similar survival behaviour regardless of the original PAM50 assignment. We propose to incorporate our PAM50 uncertainty estimation to support therapeutic decisions. Availability and Implementation: Source code can be found in 'pbcmc' R package at Bioconductor. Contacts: cristobalfresno@gmail.com or efernandez@bdmg.com.ar. Supplementary information: Supplementary data are available at Bioinformatics online.

TarSeqQC: Quality control on targeted sequencing experiments in R.

Targeted sequencing (TS) is growing as a screening methodology used in research and medical genetics to identify genomic alterations causing human diseases. In general, a list of possible genomic variants is derived from mapped reads through a variant calling step. This processing step is usually based on variant coverage, although it may be affected by several factors. Therefore, undercovered relevant clinical variants may not be reported, affecting pathology diagnosis or treatment. Thus, a prior quality control of the experiment is critical to determine variant detection accuracy and to avoid erroneous medical conclusions. There are several quality control tools, but they are focused on issues related to whole-genome sequencing. However, in TS, quality control should assess experiment, gene, and genomic region performances based on achieved coverages. Here, we propose TarSeqQC R package for quality control in TS experiments. The tool is freely available at Bioconductor repository. TarSeqQC was used to analyze two datasets; low-performance primer pools and features were detected, enhancing the quality of experiment results. Read count profiles were also explored, showing TarSeqQC's effectiveness as an exploration tool. Our proposal may be a valuable bioinformatic tool for routinely TS experiments in both research and medical genetics.

Establishment and Comprehensive Characterization of a Novel Preclinical Platform of Metastatic Retinoblastoma for Therapeutic Developments.

Purpose: Although there have been improvements in the management of metastatic retinoblastoma, most patients do not survive, and all patients suffer from multiple short- and long-term treatment toxicities. Reliable and informative models to assist clinicians are needed. Thus we developed and comprehensively characterized a novel preclinical platform of primary cell cultures and xenograft models of metastatic retinoblastoma to provide insights into the molecular biology underlying metastases and to perform drug screening for the identification of hit candidates with the highest potential for clinical translation. Methods: Orbital tumor, bone marrow, cerebrospinal fluid, and lymph node tumor infiltration specimens were obtained from seven patients with metastatic retinoblastoma at diagnosis, disease progression, or relapse. Tumor specimens were engrafted in immunodeficient animals, and primary cell lines were established. Genomic, immunohistochemical/immunocytochemical, and pharmacological analysis were performed. Results: We successfully established five primary cell lines: two derived from leptomeningeal, two from orbital, and one from lymph node tumor dissemination. After the intravitreal or intraventricular inoculation of these cells, we established cell-derived xenograft models. Both primary cell lines and xenografts accurately retained the histological and genomic features of the tumors from which they were derived and faithfully recapitulated the dissemination patterns and pharmacological sensitivity observed in the matched patients. Conclusions: Ours is an innovative and thoroughly characterized preclinical platform of metastatic retinoblastoma developed for the understanding of tumor biology of this highly aggressive tumor and has the potential to identify drug candidates to treat patients who currently lack effective treatment options.

Exome and Tissue-Associated Microbiota as Predictive Markers of Response to Neoadjuvant Treatment in Locally Advanced Rectal Cancer.

The clinical and pathological responses to multimodal neoadjuvant therapy in locally advanced rectal cancers (LARCs) remain unpredictable, and robust biomarkers are still lacking. Recent studies have shown that tumors present somatic molecular alterations related to better treatment response, and it is also clear that tumor-associated bacteria are modulators of chemotherapy and immunotherapy efficacy, therefore having implications for long-term survivorship and a good potential as the biomarkers of outcome. Here, we performed whole exome sequencing and 16S ribosomal RNA (rRNA) amplicon sequencing from 44 pre-treatment LARC biopsies from Argentinian and Brazilian patients, treated with neoadjuvant chemoradiotherapy or total neoadjuvant treatment, searching for predictive biomarkers of response (responders, n = 17; non-responders, n = 27). In general, the somatic landscape of LARC was not capable to predict a response; however, a significant enrichment in mutational signature SBS5 was observed in non-responders (p = 0.0021), as well as the co-occurrence of APC and FAT4 mutations (p < 0.05). Microbiota studies revealed a similar alpha and beta diversity of bacteria between response groups. Yet, the linear discriminant analysis (LDA) of effect size indicated an enrichment of Hungatella, Flavonifractor, and Methanosphaera (LDA score ≥3) in the pre-treatment biopsies of responders, while non-responders had a higher abundance of Enhydrobacter, Paraprevotella (LDA score ≥3) and Finegoldia (LDA score ≥4). Altogether, the evaluation of these biomarkers in pre-treatment biopsies could eventually predict a neoadjuvant treatment response, while in post-treatment samples, it could help in guiding non-operative treatment strategies.

Socioeconomic, Clinical, and Molecular Features of Breast Cancer Influence Overall Survival of Latin American Women.

Molecular profile of breast cancer in Latin-American women was studied in five countries: Argentina, Brazil, Chile, Mexico, and Uruguay. Data about socioeconomic characteristics, risk factors, prognostic factors, and molecular subtypes were described, and the 60-month overall cumulative survival probabilities (OS) were estimated. From 2011 to 2013, 1,300 eligible Latin-American women 18 years or older, with a diagnosis of breast cancer in clinical stage II or III, and performance status ≦̸1 were invited to participate in a prospective cohort study. Face-to-face interviews were conducted, and clinical and outcome data, including death, were extracted from medical records. Unadjusted associations were evaluated by Chi-squared and Fisher's exact tests and the OS by Kaplan-Meier method. Log-rank test was used to determine differences between cumulative probability curves. Multivariable adjustment was carried out by entering potential confounders in the Cox regression model. The OS at 60 months was 83.9%. Multivariable-adjusted death hazard differences were found for women living in Argentina (2.27), Chile (1.95), and Uruguay (2.42) compared with Mexican women, for older (≥60 years) (1.84) compared with younger (≤40 years) women, for basal-like subtype (5.8), luminal B (2.43), and HER2-enriched (2.52) compared with luminal A subtype, and for tumor clinical stages IIB (1.91), IIIA (3.54), and IIIB (3.94) compared with stage IIA women. OS was associated with country of residence, PAM50 intrinsic subtype, age, and tumor stage at diagnosis. While the latter is known to be influenced by access to care, including cancer screening, timely diagnosis and treatment, including access to more effective treatment protocols, it may also influence epigenetic changes that, potentially, impact molecular subtypes. Data derived from heretofore understudied populations with unique geographic ancestry and sociocultural experiences are critical to furthering our understanding of this complexity.

The Transcriptomic Portrait of Locally Advanced Breast Cancer and Its Prognostic Value in a Multi-Country Cohort of Latin American Patients.

Purposes: Most molecular-based published studies on breast cancer do not adequately represent the unique and diverse genetic admixture of the Latin American population. Searching for similarities and differences in molecular pathways associated with these tumors and evaluating its impact on prognosis may help to select better therapeutic approaches. Patients and Methods: We collected clinical, pathological, and transcriptomic data of a multi-country Latin American cohort of 1,071 stage II-III breast cancer patients of the Molecular Profile of Breast Cancer Study (MPBCS) cohort. The 5-year prognostic ability of intrinsic (transcriptomic-based) PAM50 and immunohistochemical classifications, both at the cancer-specific (OSC) and disease-free survival (DFS) stages, was compared. Pathway analyses (GSEA, GSVA and MetaCore) were performed to explore differences among intrinsic subtypes. Results: PAM50 classification of the MPBCS cohort defined 42·6% of tumors as LumA, 21·3% as LumB, 13·3% as HER2E and 16·6% as Basal. Both OSC and DFS for LumA tumors were significantly better than for other subtypes, while Basal tumors had the worst prognosis. While the prognostic power of traditional subtypes calculated with hormone receptors (HR), HER2 and Ki67 determinations showed an acceptable performance, PAM50-derived risk of recurrence best discriminated low, intermediate and high-risk groups. Transcriptomic pathway analysis showed high proliferation (i.e. cell cycle control and DNA damage repair) associated with LumB, HER2E and Basal tumors, and a strong dependency on the estrogen pathway for LumA. Terms related to both innate and adaptive immune responses were seen predominantly upregulated in Basal tumors, and, to a lesser extent, in HER2E, with respect to LumA and B tumors. Conclusions: This is the first study that assesses molecular features at the transcriptomic level in a multicountry Latin American breast cancer patient cohort. Hormone-related and proliferation pathways that predominate in PAM50 and other breast cancer molecular classifications are also the main tumor-driving mechanisms in this cohort and have prognostic power. The immune-related features seen in the most aggressive subtypes may pave the way for therapeutic approaches not yet disseminated in Latin America. Clinical Trial Registration: ClinicalTrials.gov (Identifier: NCT02326857).

Clinical and Genetic Spectrum of Stargardt Disease in Argentinean Patients.

PURPOSE: To describe the clinical and molecular spectrum of Stargardt disease (STGD) in a cohort of Argentinean patients. METHODS: This retrospective study included 132 subjects comprising 95 probands clinically diagnosed with STGD and relatives from 16 of them. Targeted next-generation sequencing of the coding and splicing regions of ABCA4 and other phenocopying genes (ELOVL4, PROM1, and CNGB3) was performed in 97 STGD patients. RESULTS: We found two or more disease-causing variants in the ABCA4 gene in 69/95 (73%) probands, a single ABCA4 variant in 9/95 (9.5%) probands, and no ABCA4 variants in 17/95 (18%) probands. The final analysis identified 173 variants in ABCA4. Seventy-nine ABCA4 variants were unique, of which nine were novel. No significant findings were seen in the other evaluated genes. CONCLUSION: This study describes the phenotypic and genetic features of STGD1 in an Argentinean cohort. The mutations p.(Gly1961Glu) and p.(Arg1129Leu) were the most frequent, representing almost 20% of the mutated alleles. We also expanded the ABCA4 mutational spectrum with nine novel disease-causing variants, of which eight might be associated with South American natives.

Prognostic Impact of An Integrative Landscape of Clinical, Immune, and Molecular Features in Non-Metastatic Rectal Cancer.

Rectal Cancer (RC) is a complex disease that involves highly variable treatment responses. Currently, there is a lack of reliable markers beyond TNM to deliver a personalized treatment in a cancer setting where the goal is a curative treatment. Here, we performed an integrated characterization of the predictive and prognostic role of clinical features, mismatch-repair deficiency markers, HER2, CDX2, PD-L1 expression, and CD3-CD8+ tumor-infiltrating lymphocytes (TILs) coupled with targeted DNA sequencing of 76 non-metastatic RC patients assigned to total mesorectal excision upfront (TME; n = 15) or neoadjuvant chemo-radiotherapy treatment (nCRT; n = 61) followed by TME. Eighty-two percent of RC cases displayed mutations affecting cancer driver genes such as TP53, APC, KRAS, ATM, and PIK3CA. Good response to nCRT treatment was observed in approximately 40% of the RC cases, and poor pathological tumor regression was significantly associated with worse disease-free survival (DFS, HR = 3.45; 95%CI = 1.14-10.4; p = 0.028). High neutrophils-platelets score (NPS) (OR = 10.52; 95%CI=1.34-82.6; p = 0.025) and KRAS mutated cases (OR = 5.49; 95%CI = 1.06-28.4; p = 0.042) were identified as independent predictive factors of poor response to nCRT treatment in a multivariate analysis. Furthermore, a Cox proportional-hazard model showed that the KRAS mutational status was an independent prognostic factor associated with higher risk of local recurrence (HR = 9.68; 95%CI = 1.01-93.2; p <0.05) and shorter DFS (HR = 2.55; 95%CI = 1.05-6.21; p <0.05), while high CEA serum levels were associated with poor DFS (HR = 2.63; 95%CI = 1.01-6.85; p <0.05). Integrated clinical and molecular-based unsupervised analysis allowed us to identify two RC prognostic groups (cluster 1 and cluster 2) associated with disease-specific OS (HR = 20.64; 95%CI = 2.63-162.2; p <0.0001), metastasis-free survival (HR = 3.67; 95%CI = 1.22-11; p = 0.012), local recurrence-free survival (HR = 3.34; 95%CI = 0.96-11.6; p = 0.043) and worse DFS (HR = 2.68; 95%CI = 1.18-6.06; p = 0.012). The worst prognosis cluster 2 was enriched by stage III high-risk clinical tumors, poor responders to nCRT, with low TILs density and high frequency of KRAS and TP53 mutated cases compared with the best prognosis cluster 1 (p <0.05). Overall, this study provides a comprehensive and integrated characterization of non-metastatic RC cases as a new insight to deliver a personalized therapeutic approach.

Recurrent Somatic Chromosomal Abnormalities in Relapsed Extraocular Retinoblastoma.

Most reports about copy number alterations (CNA) in retinoblastoma relate to patients with intraocular disease and features of children with extraocular relapse remain unknown, so we aimed to describe the CNA in this population. We evaluated 23 patients and 27 specimens from 4 centers. Seventeen cases had extraocular relapse after initial enucleation and six cases after an initial preservation attempt. We performed an analysis of CNA and BCOR gene alteration by SNP array (Single Nucleotide Polymorfism array), whole-exome sequencing, IMPACT panel and CGH array (Array-based comparative genomic hybridization). All cases presented CNA at a higher prevalence than those reported in previously published studies for intraocular cases. CNA previously reported for intraocular retinoblastoma were found at a high frequency in our cohort: gains in 1q (69.5%), 2p (60.9%) and 6p (86.9%), and 16q loss (78.2%). Other, previously less-recognized, CNA were found including loss of 11q (34.8%), gain of 17q (56.5%), loss of 19q (30.4%) and BCOR alterations were present in 72.7% of our cases. A high number of CNA including 11q deletions, 17q gains, 19q loss, and BCOR alterations, are more common in extraocular retinoblastoma. Identification of these features may be correlated with a more aggressive tumor warranting consideration for patient management.

A Single Dose of a Hybrid hAdV5-Based Anti-COVID-19 Vaccine Induces a Long-Lasting Immune Response and Broad Coverage against VOC.

Most approved vaccines against COVID-19 have to be administered in a prime/boost regimen. We engineered a novel vaccine based on a chimeric human adenovirus 5 (hAdV5) vector. The vaccine (named CoroVaxG.3) is based on three pillars: (i) high expression of Spike to enhance its immunodominance by using a potent promoter and an mRNA stabilizer; (ii) enhanced infection of muscle and dendritic cells by replacing the fiber knob domain of hAdV5 by hAdV3; (iii) use of Spike stabilized in a prefusion conformation. The transduction with CoroVaxG.3-expressing Spike (D614G) dramatically enhanced the Spike expression in human muscle cells, monocytes and dendritic cells compared to CoroVaxG.5 that expressed the native fiber knob domain. A single dose of CoroVaxG.3 induced a potent humoral immunity with a balanced Th1/Th2 ratio and potent T-cell immunity, both lasting for at least 5 months. Sera from CoroVaxG.3-vaccinated mice was able to neutralize pseudoviruses expressing B.1 (wild type D614G), B.1.117 (alpha), P.1 (gamma) and B.1.617.2 (delta) Spikes, as well as an authentic P.1 SARS-CoV-2 isolate. Neutralizing antibodies did not wane even after 5 months, making this kind of vaccine a likely candidate to enter clinical trials.

Pan-Cancer Molecular Patterns and Biological Implications Associated with a Tumor-Specific Molecular Signature.

Studying tissue-independent components of cancer and defining pan-cancer subtypes could be addressed using tissue-specific molecular signatures if classification errors are controlled. Since PAM50 is a well-known, United States Food and Drug Administration (FDA)-approved and commercially available breast cancer signature, we applied it with uncertainty assessment to classify tumor samples from over 33 cancer types, discarded unassigned samples, and studied the emerging tumor-agnostic molecular patterns. The percentage of unassigned samples ranged between 55.5% and 86.9% in non-breast tissues, and gene set analysis suggested that the remaining samples could be grouped into two classes (named C1 and C2) regardless of the tissue. The C2 class was more dedifferentiated, more proliferative, with higher centrosome amplification, and potentially more TP53 and RB1 mutations. We identified 28 gene sets and 95 genes mainly associated with cell-cycle progression, cell-cycle checkpoints, and DNA damage that were consistently exacerbated in the C2 class. In some cancer types, the C1/C2 classification was associated with survival and drug sensitivity, and modulated the prognostic meaning of the immune infiltrate. Our results suggest that PAM50 could be repurposed for a pan-cancer context when paired with uncertainty assessment, resulting in two classes with molecular, biological, and clinical implications.

Pre-Existing Tumoral B Cell Infiltration and Impaired Genome Maintenance Correlate with Response to Chemoradiotherapy in Locally Advanced Rectal Cancer.

Locally advanced rectal cancer (LARC) remains a medical challenge. Reliable biomarkers to predict which patients will significantly respond to neoadjuvant chemoradiotherapy (nCRT) have not been identified. We evaluated baseline genomic and transcriptomic features to detect differences that may help predict response to nCRT. Eligible LARC patients received nCRT (3D-LCRT 50.4 Gy plus capecitabine 825 mg/m2/bid), preceded by three cycles of CAPOX in high systemic-relapse risk tumors, and subsequent surgery. Frozen tumor biopsies at diagnosis were sequenced using a colorectal cancer panel. Transcriptomic data was used for pathway and cell deconvolution inferential algorithms, coupled with immunohistochemical validation. Clinical and molecular data were analyzed according to nCRT outcome. Pathways related to DNA repair and proliferation (p < 0.005), and co-occurrence of RAS and TP53 mutations (p = 0.001) were associated with poor response. Enrichment of expression signatures related to enhanced immune response, particularly B cells and interferon signaling (p < 0.005), was detected in good responders. Immunohistochemical analysis of CD20+ cells validated the association of good response with B cell infiltration (p = 0.047). Findings indicate that the presence of B cells is associated with successful tumor regression following nCRT in LARC. The prevalence of simultaneous RAS and TP53 mutations along with a proficient DNA repair system that may counteract chemoradio-induced DNA damage was associated with poor response.

Genomic and Transcriptomic Tumor Heterogeneity in Bilateral Retinoblastoma.

Importance: Comprehensive understanding of the genomic and gene-expression differences between retinoblastoma tumors from patients with bilateral disease may help to characterize risk and optimize treatment according to individual tumor characteristics. Objective: To compare the genomic features between each eye and a specimen from an orbital relapse in patients with bilateral retinoblastoma. Design, Setting, and Participants: In this case, 2 patients with retinoblastoma underwent upfront bilateral enucleation. Tumor samples were subjected to genomic and gene-expression analysis. Primary cell cultures were established from both of the tumors of 1 patient and were used for gene-expression studies. Main Outcomes and Measures: Whole-exome sequencing was performed on an Illumina platform for fresh tumor samples and DNA arrays (CytoScan or OncoScan) were used for paraffin-embedded samples and cell lines. Gene-expression analysis was performed using Agilent microarrays. Germinal and somatic alterations, copy number alterations, and differential gene expression were assessed. Results: After initial bilateral enucleation, patient 1 showed massive choroidal and laminar optic nerve infiltration, while patient 2 showed choroidal and laminar optic nerve invasion. Patient 1 developed left-eye orbital recurrence and bone marrow metastasis less than 1 year after enucleation. Both ocular tumors showed gains on 1q and 6p but presented other distinct genomic alterations, including an additional gain in 2p harboring the N-myc proto-oncogene (MYCN) in the left tumor and orbital recurrence. Similar copy number alterations between the orbital recurrence and the left eye supported the origin of the relapse, with an additional 11q loss only detected in the orbital relapse. Specimens from patient 2 showed common copy number gains and losses, but further evolution rendered a 2p gain spanning MYCN in the left tumor. For this patient, microarray expression analysis showed differential expression of the MYCN and the forkhead box protein G1 (FOXG1) gene pathways between the left and right tumors. Conclusions and Relevance: Differential genomic and gene expression features were observed between tumors in 2 patients with bilateral disease, confirming intereye heterogeneity that might be considered if targeted therapies are used in such patients. Chromosomal alteration profile supported the origin of the orbital recurrence from the homolateral eye in 1 patient. Loss in chromosome 11q may have been associated with extraocular relapse in this patient.

Clinical, Genomic, and Pharmacological Study of MYCN-Amplified RB1 Wild-Type Metastatic Retinoblastoma.

An uncommon subgroup of unilateral retinoblastomas with highly aggressive histological features, lacking aberrations in RB1 gene with high-level amplification of MYCN (MCYNamplRB1+/+) has only been described as intra-ocular cases treated with initial enucleation. Here, we present a comprehensive clinical, genomic, and pharmacological analysis of two cases of MCYNamplRB1+/+ with orbital and cervical lymph node involvement, but no central nervous system spread, rapidly progressing to fatal disease due to chemoresistance. Both patients showed in common MYCN high amplification and chromosome 16q and 17p loss. A somatic mutation in TP53, in homozygosis by LOH, and high chromosomal instability leading to aneuploidy was identified in the primary ocular tumor and sites of dissemination of one patient. High-throughput pharmacological screening was performed in a primary cell line derived from the lymph node dissemination of one case. This cell line showed resistance to broad spectrum chemotherapy consistent with the patient's poor response but sensitivity to the synergistic effects of panobinostat-bortezomib and carboplatin-panobinostat associations. From these cells we established a cell line derived xenograft model that closely recapitulated the tumor dissemination pattern of the patient and served to evaluate whether triple chemotherapy significantly prolonged survival of the animals. We report novel genomic alterations in two cases of metastatic MCYNamplRB1+/+ that may be associated with chemotherapy resistance and in vitro/in vivo models that serve as basis for tailoring therapy in these cases.

Improving 2D-DIGE protein expression analysis by two-stage linear mixed models: assessing experimental effects in a melanoma cell study.

MOTIVATION: Difference in-gel electrophoresis (DIGE)-based protein expression analysis allows assessing the relative expression of proteins in two biological samples differently labeled (Cy5, Cy3 CyDyes). In the same gel, a reference sample is also used (Cy2 CyDye) for spot matching during image analysis and volume normalization. The standard statistical techniques to identify differentially expressed (DE) proteins are the calculation of fold-changes and the comparison of treatment means by the t-test. The analyses rarely accounts for other experimental effects, such as CyDye and gel effects, which could be important sources of noise while detecting treatment effects. RESULTS: We propose to identify DIGE DE proteins using a two-stage linear mixed model. The proposal consists of splitting the overall model for the measured intensity into two interconnected models. First, we fit a normalization model that accounts for the general experimental effects, such as gel and CyDye effects as well as for the features of the associated random term distributions. Second, we fit a model that uses the residuals from the first step to account for differences between treatments in protein-by-protein basis. The modeling strategy was evaluated using data from a melanoma cell study. We found that a heteroskedastic model in the first stage, which also account for CyDye and gel effects, best normalized the data, while allowing for an efficient estimation of the treatment effects. The Cy2 reference channel was used as a covariate in the normalization model to avoid skewness of the residual distribution. Its inclusion improved the detection of DE proteins in the second stage.