IGHV Mutational Status in a Cohort of Bulgarian CLL Patients: High Unmutated CLL Prevalence in North-East Bulgaria.

Chronic lymphocytic leukemia (CLL) is the most common leukemia in adults. One of the best established CLL prognostic markers is the somatic hypermutational status of the IGHV gene which is a part of the immunoglobulin heavy chain variable region. Technology for IGHV genotyping has been optimized and has been applied in routine diagnostics for the first time in Bulgaria. A total of 105 patients with CLL from different Bulgarian regions were tested. IGHV mutational status was determined by Sanger sequencing on total genomic DNA (gDNA) or RNA extracted from mononuclear cells. All sequencing profiles were analyzed with the IMGT/V-QUEST tool. Within the course of the analysis a high percentage of IGHV unmutated status was established in the Varna district on the Black Sea (Northeast Bulgaria). In addition, the IGHV genotyping performed on gDNA revealed a rare case with multiple rearrangements. The present data from IGHV genotyping will help in choosing the proper treatment for the benefit of Bulgarian CLL patients.

Clinical characteristic and survival outcomes of patients with advanced NSCLC according to KRAS mutational status in the French real-life ESME cohort.

PURPOSE: The RAS/MEK signaling pathway is essential in carcinogenesis and frequently altered in non-small-cell lung cancer (NSCLC), notably by KRAS mutations (KRASm) that affect 25%-30% of non-squamous NSCLC. This study aims to explore the impact of KRASm subtypes on disease phenotype and survival outcomes. PATIENTS AND METHODS: We conducted a retrospective analysis of the French Epidemiological Strategy and Medical Economics database for advanced or metastatic lung cancer from 2011 to 2021. Patient demographics, histology, KRASm status, treatment strategies, and outcomes were assessed. RESULTS: Of 10 177 assessable patients for KRAS status, 17.6% had KRAS p.G12C mutation, 22.6% had KRAS non-p.G12C mutation, and 59.8% were KRASwt. KRASm patients were more often smokers (96.3%) compared with KRASwt (85.8%). A higher proportion of programmed death-ligand 1 ≥50% was found for KRASm patients: 43.5% versus 38.0% (P < 0.01). KRASm correlated with poorer outcomes. First-line median progression-free survival was shorter in the KRASm than the KRASwt cohort: 4.0 months [95% confidence interval (CI) 3.7-4.3 months] versus 5.1 months (95% CI 4.8-5.3 months), P < 0.001. First-line overall survival was shorter for KRASm than KRASwt patients: 12.6 months (95% CI 11.6-13.6 months) versus 15.4 months (95% CI 14.6-16.2 months), P = 0.012. First-line chemoimmunotherapy offered better overall survival in KRAS p.G12C (48.8 months) compared with KRAS non-p.G12C (24.0 months) and KRASwt (22.5 months) patients. Second-line overall survival with immunotherapy was superior in the KRAS p.G12C subgroup: 12.6 months (95% CI 8.1-18.6 months) compared with 9.4 months (95% CI 8.0-11.4 months) for KRAS non-p.G12C and 9.6 months (8.4-11.0 months) for KRASwt patients. CONCLUSION: We highlighted distinct clinical profiles and survival outcomes according to KRASm subtypes. Notably KRAS p.G12C mutations may provide increased sensitivity to immunotherapy, suggesting potential therapeutic implications for sequencing or combination of therapies. Further research on the impact of emerging KRAS specific inhibitors are warranted in real-world cohorts.

Unmutated IGHV at diagnosis in patients with early stage CLL independently predicts for shorter follow-up time to first treatment (TTFT).

The mutational status of the IGHV gene is routinely assessed in patients with chronic lymphocytic leukaemia (CLL), since it is both prognostic of clinical outcome and predictive of response to treatment. This study evaluates the IGHV mutational status, assessed in newly diagnosed CLL patients, as a stand-alone predictor of time to first treatment (TTFT). We analysed the data of 236 CLL patients, diagnosed at our centre between January 2004 and September 2020, with a minimum follow-up period of 3.0 years, Binet A-B and Rai 0-II stages. IGHV was unmutated in 38.1 % and mutated in 61.9 % of cases. The univariate analysis showed a statistically significant difference (p < 0.001) in TTFT based on unmutated (85.2 % at 14 years, 95 % CI = 63.3-94.5 %) or mutated (41.3 % at 14 years, 95 % CI = 29.5-51.8 %) and the need for treatment at 1, 3 and 5 years was of 20.0 % vs 4.1 % (p < 0.001), 42.7 % vs 11.4 % (p < 0.001) and 55.8 % vs 20.0 % (p < 0.001) in unmutated and mutated IGHV patients, respectively. Multivariate analysis confirmed that unmutated IGHV status negatively affects TTFT (p < 0.001), in addition to high-risk genomic aberration (p = 0.025), Rai stage I (p = 0.007) and II (p-value < 0.001). The difference in TTFT based on unmutated or mutated IGHV status remains statistically significant also when considering the subgroups by the genomic aberrations and Rai stages. Our findings suggest that, with the single analysis of the IGHV mutational status at CLL diagnosis, along with clinical and laboratory data, and without karyotype and TP53 data, clinicians will have prognostic and predictive indications for the first clinical treatment and appropriate follow-up of patients.

Machine learning and radiomics analysis by computed tomography in colorectal liver metastases patients for RAS mutational status prediction.

PURPOSE: To assess the efficacy of machine learning and radiomics analysis by computed tomography (CT) in presurgical setting, to predict RAS mutational status in colorectal liver metastases. METHODS: Patient selection in a retrospective study was carried out from January 2018 to May 2021 considering the following inclusion criteria: patients subjected to surgical resection for liver metastases; proven pathological liver metastases; patients subjected to enhanced CT examination in the presurgical setting with a good quality of images; and RAS assessment as standard reference. A total of 851 radiomics features were extracted using the PyRadiomics Python package from the Slicer 3D image computing platform after slice-by-slice segmentation on CT portal phase by two expert radiologists of each individual liver metastasis performed first independently by the individual reader and then in consensus. Balancing technique was performed, and inter- and intraclass correlation coefficients were calculated to assess the between-observer and within-observer reproducibility of features. Receiver operating characteristics (ROC) analysis with the calculation of area under the ROC curve (AUC), sensitivity (SENS), specificity (SPEC), positive predictive value (PPV), negative predictive value (NPV) and accuracy (ACC) were assessed for each parameter. Linear and non-logistic regression model (LRM and NLRM) and different machine learning-based classifiers were considered. Moreover, features selection was performed before and after a normalized procedure using two different methods (3-sigma and z-score). RESULTS: Seventy-seven liver metastases in 28 patients with a mean age of 60 years (range 40-80 years) were analyzed. The best predictors, at univariate analysis for both normalized procedures, were original_shape_Maximum2DDiameter and wavelet_HLL_glcm_InverseVariance that reached an accuracy of 80%, an AUC ≥ 0.75, a sensitivity ≥ 80% and a specificity ≥ 70% (p value < < 0.01). However, a multivariate analysis significantly increased the accuracy in RAS prediction when a linear regression model (LRM) was used. The best performance was obtained using a LRM combining linearly 12 robust features after a z-score normalization procedure: AUC of 0.953, accuracy 98%, sensitivity 96%, specificity of 100%, PPV 100% and NPV 96% (p value < < 0.01). No statistically significant increase was obtained considering the tested machine learning both without normalization and with normalization methods. CONCLUSIONS: Normalized approach in CT radiomics analysis allows to predict RAS mutational status in colorectal liver metastases patients.

Clinical and molecular heterogeneity associated with tumor sidedness in colorectal liver metastasis: a multicenter propensity cohort study.

Background: Colorectal liver metastasis (CRLM) exhibits highly heterogeneity, with clinically and molecularly defined subgroups that differ in their prognosis. The aim of this study is to explore whether left-sided tumors is clinically and gnomically distinct from right-sided tumors in CRLM. Methods: This retrospective study included 1,307 patients who underwent primary tumor and metastases resection at three academic centers in China from January 1, 2012, to December 31, 2020. Propensity score matching with 1:1 ratio matching was performed. The prognostic impact of tumor sidedness was determined after stratifying by the KRAS mutational status. Moreover, whole-exome sequencing (WES) of 200 liver tumor tissues were performed to describe the heterogeneity across the analysis of somatic and germline profiles. Results: The median follow-up was 68 months. Matching yielded 481 pairs of patients. Compared to right-sided CRLM, left-sided patients experienced with better 5-year overall survival (OS) in surgery responsiveness, with a 14.6 lower risk of death [hazard ratio (HR), 1.36, 95% confidence interval (CI), 1.10-1.69, P=0.004]. Interaction between tumor sidedness and KRAS status was statistically significant: left-sidedness was associated with better prognosis among KRAS wild-type patients (HR 1.71; 95% CI: 1.20-2.45; P=0.003), but not among KRAS mutated-type patients. Integrated molecular analyses showed that right-sided tumors more frequently harbored TP53, APC, KRAS, and BRAF alterations, and identified a critical role of KRAS mutation in correlation with their survival differences. Higher pathogenic germline variants were identified in the right-sided tumors compared with left-sided tumors (29.3% vs. 15.5%, P=0.03). Conclusions: We demonstrated that the prognostic impacts of tumor sidedness in CRLM is restricted patients with KRAS wild-type tumors. Tumor sidedness displays considerable clinical and molecular heterogeneity that may associate with their therapy benefits and prognosis.

Chronic Lymphocytic Leukemia (CLL) with Borderline Immunoglobulin Heavy Chain Mutational Status, a Rare Subgroup of CLL with Variable Disease Course.

Chronic lymphocytic leukemia (CLL) exhibits substantial variability in disease course. The mutational status of the B-cell receptor immunoglobulin heavy variable (IGHV) chain is a critical prognostic factor, categorizing patients into mutated (M-IGHV) and unmutated (U-IGHV) groups. Recently, a third subgroup with borderline mutational status (BL-IGHV) has been identified, comprising approximately 5% of CLL cases. This study retrospectively analyzes the outcomes of 30 BL-IGHV mutated patients among a cohort of 653 CLL patients, focusing on time to first treatment (TTFT) and overall survival (OS). BL-IGHV patients had a short TTFT similar to U-IGHV patients (median 30.2 vs. 34 months; p = 0.9). Conversely, the OS of BL-IGHV patients resembled M-IGHV patients (median NR vs. 258 months; p = 1). Despite a similar incidence in unfavorable prognostic factors, the TTFT was shorter compared to other published cohorts. However, striking similarities with other experiences suggest that BL-IGHV mutated patients share common biological characteristics, biased IGHV gene usage and BCR subset frequency. These findings also underscore the need for multicentric efforts aggregating data on BL-IGHV CLL in order to elucidate its disease course and optimize therapeutic approaches for this rare subgroup. Until then, predicting outcomes and optimal management of BL-IGHV CLL will remain challenging.

Machine learning-based radiomics analysis in predicting RAS mutational status using magnetic resonance imaging.

PURPOSE: To assess the efficacy of radiomics features, obtained by magnetic resonance imaging (MRI) with hepatospecific contrast agent, in pre-surgical setting, to predict RAS mutational status in liver metastases. METHODS: Patients with MRI in pre-surgical setting were enrolled in a retrospective study. Manual segmentation was made by means 3D Slicer image computing, and 851 radiomics features were extracted as median values using the PyRadiomics Python package. The features were extracted considering the agreement with the Imaging Biomarker Standardization Initiative (IBSI). Balancing was performed through synthesis of samples for the underrepresented classes using the self-adaptive synthetic oversampling (SASYNO) approach. Inter- and intraclass correlation coefficients (ICC) were calculated to assess the between-observer and within-observer reproducibility of all radiomics characteristics. For continuous variables, nonparametric Wilcoxon-Mann-Whitney test was utilized. Benjamini and Hochberg's false discovery rate (FDR) adjustment for multiple testing was used. Receiver operating characteristics (ROC) analysis with the calculation of area under the ROC curve (AUC), sensitivity (SENS), specificity (SPEC), positive predictive value (PPV), negative predictive value (NPV) and accuracy (ACC) were assessed for each parameter. Linear and non-logistic regression model (LRM and NLRM) and different machine learning-based classifiers including decision tree (DT), k-nearest neighbor (KNN) and support vector machine (SVM) were considered. Moreover, features selection were performed before and after a normalized procedure using two different methods (3-sigma and z-score). McNemar test was used to assess differences statistically significant between dichotomic tables. All statistical procedures were done using MATLAB R2021b Statistics and Machine Toolbox (MathWorks, Natick, MA, USA). RESULTS: Seven normalized radiomics features, extracted from arterial phase, 11 normalized radiomics features, from portal phase, 12 normalized radiomics features from hepatobiliary phase and 12 normalized features from T2-W SPACE sequence were robust predictors of RAS mutational status. The multivariate analysis increased significantly the accuracy in RAS prediction when a LRM was used, combining 12 robust normalized features extracted by VIBE hepatobiliary phase reaching an accuracy of 99%, a sensitivity 97%, a specificity of 100%, a PPV of 100% and a NPV of 98%. No statistically significant increase was obtained, considering the tested classifiers DT, KNN and SVM, both without normalization and with normalization methods. CONCLUSIONS: Normalized approach in MRI radiomics analysis allows to predict RAS mutational status.

Emerging role of liquid biopsy in rat sarcoma virus mutated metastatic colorectal cancer: A case report.

BACKGROUND: In patients with metastatic colorectal cancer (mCRC), the treatment options are limited and have been proved to be affected by rat sarcoma virus (RAS) mutational status. In RAS wild-type (wt) patients, the combination of anti-epidermal growth factor receptor (EGFR) monoclonal antibodies with chemotherapy (CT) is more effective than CT alone. On the other hand, RAS-mutated patients are not eligible for treatment with anti-EGFR antibodies. CASE SUMMARY: Eleven patients with initially RAS-mutated mCRC were followed from diagnosis to May 2022. At the time of cell-free DNA determination, five patients had undergone one CT line, five patients had undergone two CT lines, and one patient had undergone three CT lines (all in combination with bevacizumab). At the second and third treatment lines [second line (2L), third line (3L)], patients with neo-RAS wt received a combination of CT and cetuximab. In neo-RAS wt patients treated with anti-EGFR, our findings indicated an increase in progression-free survival for both 2L and 3L (14.5 mo, P = 0.119 and 3.9 mo, P = 0.882, respectively). Regarding 2L overall survival, we registered a slight increase in neo-RAS wt patients treated with anti-EGFR (33.6 mo vs 32.4 mo, P = 0.385). At data cut-off, two patients were still alive: A RAS-mutated patient undergoing 3L treatment and a neo-RAS wt patient who received 2L treatment with anti-EGFR (ongoing). CONCLUSION: Our case series demonstrated that monitoring RAS mutations in mCRC by liquid biopsy may provide an additional treatment line for neo-RAS wt patients.

HPV-negative head and neck cancers with adverse pathological features carry specific molecular changes that are associated with survival.

BACKGROUND: Adverse pathological features following surgery in head and neck squamous cell carcinoma (HNSCC) are strongly associated with survival and guide adjuvant therapy. We investigated molecular changes associated with these features. METHODS: We downloaded data from the Cancer Genome Atlas and Cancer Proteome Atlas HNSCC cohorts. We compared tumors positive versus negative for perineural invasion (PNI), lymphovascular invasion (LVI), extracapsular spread (ECS), and positive margins (PSM), with multivariable analysis. RESULTS: All pathological features were associated with poor survival, as were the following molecular changes: low cyclin E1 (HR = 1.7) and high PKC-alpha (HR = 1.8) in tumors with PNI; six of 13 protein abundance changes with LVI; greater tumor hypoxia and high Raptor (HR = 2.0) and Rictor (HR = 1.6) with ECS; and low p38 (HR = 2.3), high fibronectin (HR = 1.6), low annexin A1 (HR = 3.1), and high caspase-9 (HR = 1.6) abundances with PSM. CONCLUSIONS: Pathological features in HNSCC carry specific molecular changes that may explain their poor prognostic associations.

Prediction of Glioma Grade and IDH Status Using 18F-FET PET/CT Dynamic and Multiparametric Texture Analysis.

Mutations in isocitrate dehydrogenase (IDH) represent an independent predictor of better survival in patients with gliomas. We aimed to assess grade and IDH mutation status in patients with untreated gliomas, by evaluating the respective value of 18F-FET PET/CT via dynamic and texture analyses. A total of 73 patients (male: 48, median age: 47) who underwent an 18F-FET PET/CT for initial glioma evaluation were retrospectively included. IDH status was available in 61 patients (20 patients with WHO grade 2 gliomas, 41 with grade 3-4 gliomas). Time-activity curve type and 20 parameters obtained from static analysis using LIFEx© v6.30 software were recorded. Respective performance was assessed using receiver operating characteristic curve analysis and stepwise multivariate regression analysis adjusted for patients' age and sex. The time-activity curve type and texture parameters derived from the static parameters showed satisfactory-to-good performance in predicting glioma grade and IDH status. Both time-activity curve type (stepwise OR: 101.6 (95% CI: 5.76-1791), p = 0.002) and NGLDM coarseness (stepwise OR: 2.08 × 1043 (95% CI: 2.76 × 1012-1.57 × 1074), p = 0.006) were independent predictors of glioma grade. No independent predictor of IDH status was found. Dynamic and texture analyses of 18F-FET PET/CT have limited predictive value for IDH status when adjusted for confounding factors. However, they both help predict glioma grade.

Isocitrate dehydrogenase wt and IDHmut adult-type diffuse gliomas display distinct alterations in ribosome biogenesis and 2'O-methylation of ribosomal RNA.

BACKGROUND: High-grade adult-type diffuse gliomas (HGGs) constitute a heterogeneous group of aggressive tumors that are mostly incurable. Recent advances highlighting the contribution of ribosomes to cancer development have offered new clinical perspectives. Here, we uncovered that isocitrate dehydrogenase (IDH)wt and IDHmut HGGs display distinct alterations of ribosome biology, in terms of rRNA epitranscriptomics and ribosome biogenesis, which could constitute novel hallmarks that can be exploited for the management of these pathologies. METHODS: We analyzed (1) the ribosomal RNA 2'O-ribose methylation (rRNA 2'Ome) using RiboMethSeq and in-house developed bioinformatics tools (https://github.com/RibosomeCRCL/ribomethseq-nfandrRMSAnalyzer) on 3 independent cohorts compiling 71 HGGs (IDHwt n = 30, IDHmut n = 41) and 9 non-neoplastic samples, (2) the expression of ribosome biogenesis factors using medium throughput RT-qPCR as a readout of ribosome biogenesis, and (3) the sensitivity of 5 HGG cell lines to RNA Pol I inhibitors (CX5461, BMH-21). RESULTS: Unsupervised analysis demonstrated that HGGs could be distinguished based on their rRNA 2'Ome epitranscriptomic profile, with IDHwt glioblastomas displaying the most significant alterations of rRNA 2'Ome at specific sites. In contrast, IDHmut HGGs are largely characterized by an overexpression of ribosome biogenesis factors compared to non-neoplastic tissues or IDHwt glioblastomas. Finally, IDHmut HGG-derived spheroids display higher cytotoxicity to CX5461 than IDHwt glioblastoma, while all HGG spheroids display a similar cytotoxicity to BMH-21. CONCLUSIONS: In HGGs, IDH mutational status is associated with specific alterations of the ribosome biology and with distinct sensitivities to RNA Pol I inhibitors.

Molecular characteristics in Chinese with chronic lymphocytic leukemia by next-generation sequencing: A single-center retrospective analysis.

INTRODUCTION: Although the prevalence of Asian chronic lymphocytic leukemia (CLL) patients is not as high as that of Caucasians, there are more atypical CLLs in Asia whose genetic characteristics and their clinical significance are distinct and remain unclear. METHODS: A retrospective analysis of 85 CLL samples in our center was conducted from 2019 to 2022. We used next-generation sequencing with a 172 gene panel to explore the multi-gene mutational data and the mutational status of immunoglobulin heavy variable (IGHV) gene. RESULTS: MYD88 (20.0%) was the most frequently mutated gene, much higher than in Europe, followed in order by TP53 (18.8%), NOTCH1 (14.1%), IGLL5 (11.8%), and DNMT3A (8.2%). In addition, the incidence of ATM and SF3B1 mutations was relatively lower in our centre compared to Europe. Mutated (M)-IGHV patients were more likely to have a cooccurrence of MYD88 mutation, while complex karyotype and DNMT3A mutation were more common in the unmutated (U)-IGHV group. MYD88 mutated CLL was characterized by prevalence in young males in high-risk staging, with isolated 13q deletion and concomitant mutation of IGLL5. CLL patients with MYD88 and TP53 mutation showed an unfavorable prognosis. CONCLUSION: These results would be valuable in helping to understand the characteristics and significance of cytogenetic genetics in Chinese patients with CLL.

A mutation-based radiomics signature predicts response to imatinib in Gastrointestinal Stromal Tumors (GIST).

Objectives: To develop a mutation-based radiomics signature to predict response to imatinib in Gastrointestinal Stromal Tumors (GISTs). Methods: Eighty-two patients with GIST were enrolled in this retrospective study, including 52 patients from one center that were used to develop the model, and 30 patients from a second center to validate it. Reference standard was the mutational status of tyrosine-protein kinase (KIT) and platelet-derived growth factor α (PDGFRA). Patients were dichotomized in imatinib sensitive (group 0 - mutation in KIT or PDGFRA, different from exon 18-D842V), and imatinib non-responsive (group 1 - PDGFRA exon 18-D842V mutation or absence of mutation in KIT/PDGFRA). Initially, 107 texture features were extracted from the tumor masks of baseline computed tomography scans. Different machine learning methods were then implemented to select the best combination of features for the development of the radiomics signature. Results: The best performance was obtained with the 5 features selected by the ANOVA model and the Bayes classifier, using a threshold of 0.36. With this setting the radiomics signature had an accuracy and precision for sensitive patients of 82 % (95 % CI:60-95) and 90 % (95 % CI:73-97), respectively. Conversely, a precision of 80 % (95 % CI:34-97) was obtained in non-responsive patients using a threshold of 0.9. Indeed, with the latter setting 4 patients out of 5 were correctly predicted as non-responders. Conclusions: The results are a first step towards using radiomics to improve the management of patients with GIST, especially when tumor tissue is unavailable for molecular analysis or when molecular profiling is inconclusive.

Does RAS Status Increase the Prevalence of Positive Resection Margin in Colorectal Liver Metastasis? A Systematic Review and Meta-Analysis.

BACKGROUND: Colorectal liver metastasis has a high incidence, and RAS oncogene mutation status carries significant prognostic information. We aimed to assess whether RAS-mutated patients present more or less frequently with positive margins in their hepatic metastasectomy. METHODS: We performed a systematic review and meta-analysis of studies from PubMed, Embase, and Lilacs databases. We analyzed liver metastatic colorectal cancer studies, which included information on RAS status and had surgical margin analysis of the liver metastasis. Odds ratios were computed using a random-effect model due to anticipated heterogeneity. We further performed a subanalysis limited to studies that included only patients with KRAS instead of all-RAS mutations. RESULTS: From the 2,705 studies screened, 19 articles were included in the meta-analysis. There were 7,391 patients. The prevalence of positive resection margin was not significantly different between patients carrier vs non-carrier for the all-RAS mutations (OR .99; 95% CI 0.83-1.18; P = .87), and for only KRAS mutation (OR .93; 95% CI 0.73-1.19; P = .57). CONCLUSIONS: Despite the strong correlation between colorectal liver metastasis prognosis and RAS mutation status, our meta-analysis's results suggest no correlation between the RAS status and the prevalence of positive resection margins. The findings contribute to a better understanding of the RAS mutation's role in the surgical resections of colorectal liver metastasis.

Richter transformation in Chronic Lymphocytic Leukemia.

Chronic lymphocytic leukemia can evolve to an aggressive lymphoma-in most of the cases diffuse large B cells lymphoma, rarely Hodgkin lymphoma-and this complication is defined Richter syndrome (RS). Immunogenotypic features that characterize RS include unmutated IgHV status with high prevalence of IgHV4-39/D6-13/J5 sequence; deletion of chromosome 17p or 11q; activation of oncogenes as NOTCH1 and c-MYC; inactivation of onco-suppressors as TP53 and CDKN2A; high expression of CD38 in lymph-nodes. The prognosis of this condition is very poor: patients experience a rapid clinical deterioration with frequent therapeutic failure since the current options include suboptimal strategies as standard chemo-immunotherapy followed by hematopoietic stem cells transplantation or enrollment in clinical trials which investigate the efficacy of target drugs. Understanding the biology of such a heterogeneous condition is crucial to personalize the treatment and improve patient's survival.

Patient-derived xenograft models for gastrointestinal tumors: A single-center retrospective study.

Background: Patient-derived xenograft (PDX) models have shown a great efficiency in preclinical and translational applications. Gastrointestinal (GI) tumors have a strong heterogeneity, and the engraftment rate of PDX models remarkably vary. However, the clinicopathological and molecular characteristics affecting the engraftment rate still remain elusive. Methods: A total of 312 fresh tumor tissue samples from patients with GI cancer were implanted into immunodeficient mice. The median follow-up time of patients was 37 months. Patients' characteristics were compared in terms of PDX growth and overall survival. PDX models of 3-6 generations were used for drug evaluation. Results: In total, 171 (54.8%, 171/312) PDX models were established, including 85 PDX models of colorectal cancer, 21 PDX models of esophageal cancer, and 65 PDX models of gastric cancer. Other than tumor site, histology, differentiation degree, and serum alpha-fetoprotein (AFP) level, no significant differences were found between transplantation of xenografts and patients' characteristics. For patients who had undergone neoadjuvant therapy, the incidence of tumor formation was higher in those with progressive disease (PD) or stable disease (SD). In gastric cancer, the results showed a higher transplantation rate in deficient mismatch repair (dMMR) tumors, and Ki-67 could be an important factor affecting the engraftment rate. The gene mutation status of RAS and BRAF, two important molecular markers in colorectal cancer, showed a high degree of consistency between patients' tumors and PDXs. However, no significant effects of these two mutations on PDX engraftment rate were observed. More importantly, in this study although KRAS mutations were detected in two clinical cases, evident tumor inhibition was still observed after cetuximab treatment in both PDX models and patients. Conclusion: A large-scale PDX model including 171 cases was successfully established for GI tumors in our center. The relationship between clinicopathological and molecular features and engraftment rates were clarified. Furthermore, this resource provides us with profound insights into tumor heterogeneity, making these models valuable for PDX-guided treatment decisions, and offering the PDX model as a great tool for personalized treatment and translation research.

Deep-Learning to Predict BRCA Mutation and Survival from Digital H&E Slides of Epithelial Ovarian Cancer.

BRCA 1/2 genes mutation status can already determine the therapeutic algorithm of high grade serous ovarian cancer patients. Nevertheless, its assessment is not sufficient to identify all patients with genomic instability, since BRCA 1/2 mutations are only the most well-known mechanisms of homologous recombination deficiency (HR-d) pathway, and patients displaying HR-d behave similarly to BRCA mutated patients. HRd assessment can be challenging and is progressively overcoming BRCA testing not only for prognostic information but more importantly for drugs prescriptions. However, HR testing is not already integrated in clinical practice, it is quite expensive and it is not refundable in many countries. Selecting patients who are more likely to benefit from this assessment (BRCA 1/2 WT patients) at an early stage of the diagnostic process, would allow an optimization of genomic profiling resources. In this study, we sought to explore whether somatic BRCA1/2 genes status can be predicted using computational pathology from standard hematoxylin and eosin histology. In detail, we adopted a publicly available, deep-learning-based weakly supervised method that uses attention-based learning to automatically identify sub regions of high diagnostic value to accurately classify the whole slide (CLAM). The same model was also tested for progression free survival (PFS) prediction. The model was tested on a cohort of 664 (training set: n = 464, testing set: n = 132) ovarian cancer patients, of whom 233 (35.1%) had a somatic BRCA 1/2 mutation. An area under the curve of 0.7 and 0.55 was achieved in the training and testing set respectively. The model was then further refined by manually identifying areas of interest in half of the cases. 198 images were used for training (126/72) and 87 images for validation (55/32). The model reached a zero classification error on the training set, but the performance was 0.59 in terms of validation ROC AUC, with a 0.57 validation accuracy. Finally, when applied to predict PFS, the model achieved an AUC of 0.71, with a negative predictive value of 0.69, and a positive predictive value of 0.75. Based on these analyses, we have planned further steps of development such as proving a reference classification performance, exploring the hyperparameters space for training optimization, eventually tweaking the learning algorithms and the neural networks architecture for better suiting this specific task. These actions may allow the model to improve performances for all the considered outcomes.

The Impact of KRAS Mutational Status on Long-Term Survival following Liver Resection for Hilar Cholangiocarcinoma.

KRAS mutation is reportedly associated with poor prognosis in patients with different cancer types. However, mutational data on hilar cholangiocarcinoma are few and controversial. The aim of this study was to evaluate the rate of KRAS mutations in a single-center homogeneous population resected for hilar cholangiocarcinoma and the subsequent impact on prognosis. KRAS mutation status was evaluated in 54 patients undergoing major hepatectomy combined with resection of the main biliary confluence and regional lymphadenectomy for hilar cholangiocarcinoma between 2001 and 2019. Among these 54 patients, 12 (22.2%) had a KRAS mutation. KRAS mutation was not related with pathologic characteristics of the tumor. Five-year overall survival (OS) in patients with KRAS mutation was significantly lower than that observed in patients with KRAS wild type (0 vs. 49.2%, respectively; p = 0.003). In the multivariable analysis; independent predictors of poor OS were KRAS mutation (HR = 5.384; p = 0.003) and lymph node metastases (HR = 2.805; p = 0.023). The results of our study suggested that KRAS mutation in hilar cholangiocarcinoma was not rarely observed. KRAS mutation was an independent strong predictor of poor OS. KRAS mutation analysis should be included in the routine pathologic evaluation of resected hilar cholangiocarcinoma in order to better stratify prognosis.

Spatial organization and early signaling of the B-cell receptor in CLL.

Most chronic lymphocytic leukemia (CLL) clones express B-cell receptors (BcR) of both IgM/IgD isotypes; however, 5%-10% of CLL cases express isotype-switched immunoglobulin G (IgG). The early signaling and spatial patterning of the various BcRs at steady state and after activation are still fully unresolved. Herein, we show higher expression of the BcR signalosome elements and a more robust constitutive cell-intrinsic proximal BcR signaling in CLL with unmutated IGHV expressing IgM isotype (IgM U-CLL), compared with IGHV-mutated CLL (M-CLL) expressing either IgM or IgG isotypes. IgM in U-CLL is frequently located in the membrane plane in polarized patches, occasionally in caps, and sometimes inside the cells. Among M-CLL, IgM is scattered laterally in the membrane plane in a similar pattern as seen in normal B cells, whereas IgG is dispersed around the cell membrane in smaller clusters than in IgM U-CLL. Upon BcR engagement, both IgG and IgM expressing M-CLL showed attenuated signaling and only slight spatial reorganization dynamics of BcR microclusters and internalization, compared with the extensive reorganization and internalization of the BcR in IgM expressing U-CLL. The global gene signature of IgG M-CLL was closely related to that of IgM M-CLL rather than IgM U-CLL. Overall, we report fundamental differences in the basal composition, biochemical status, and spatial organization of the BcR in the three examined immunogenetic CLL subtypes that correlate with their clinical behavior. On the basis of our findings, IgG class-switched M-CLL likely represents the same disease as IgM M-CLL rather than a different biological and/or clinical entity.

Embryologic Origin of the Primary Tumor and RAS Status Predict Survival after Resection of Colorectal Liver Metastases.

Background and objectives. In colorectal cancers, the embryologic origin of the primary tumor determines important molecular dissimilarities between right-sided (RS) and left-sided (LS) carcinomas. Although important prognostic differences have been revealed between RS- and LS-patients with resected colorectal liver metastases (CLMs), it is still unclear if this observation depends on the RAS mutational status. To refine the impact of primary tumor location (PTL) on the long-term outcomes of patients with resected CLMs, the rates of overall survival (OS), relapse-free survival (RFS) and survival after recurrence (SAR) were compared between RS- vs. LS-patients, according to their RAS status. Material and Methods. All patients with known RAS status, operated until December 2019, were selected from a prospectively maintained database, including all patients who underwent hepatectomy for histologically-proven CLMs. A log-rank test was used to compare survival rates between the RS- vs. LS-group, in RAS-mut and RAS-wt patients, respectively. A multivariate analysis was performed to assess if PTL was independently associated with OS, RFS or SAR. Results. In 53 patients with RAS-mut CLMs, the OS, RFS and SAR rates were not significantly different (p = 0.753, 0.945 and 0.973, respectively) between the RS and LS group. In 89 patients with RAS-wt CLMs, the OS and SAR rates were significantly higher (p = 0.007 and 0.001, respectively) in the LS group vs. RS group, while RFS rates were similar (p = 0.438). The multivariate analysis performed in RAS-wt patients revealed that RS primary (p = 0.009), extrahepatic metastases (p = 0.001), N-positive (p = 0.014), age higher than 65 (p = 0.002) and preoperative chemotherapy (p = 0.004) were independently associated with worse OS, while RS location (p < 0.001) and N-positive (p = 0.007) were independent prognostic factors for poor SAR. Conclusions. After resection of CLMs, PTL had no impact on long-term outcomes in RAS-mut patients, while in RAS-wt patients, the RS primary was independently associated with worse OS and SAR.