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Improved markers of prognosis are needed to stratify patients with early-stage colorectal cancer to refine selection of adjuvant therapy. The aim of the present study was to develop a biomarker of patient outcome after primary colorectal cancer resection by directly analysing scanned conventional haematoxylin and eosin stained sections using deep learning. More than 12 000 000 image tiles from patients with a distinctly good or poor disease outcome from four cohorts were used to train a total of ten convolutional neural networks, purpose-built for classifying supersized heterogeneous images. A prognostic biomarker integrating the ten networks was determined using patients with a non-distinct outcome. The marker was tested on 920 patients with slides prepared in the UK, and then independently validated according to a predefined protocol in 1122 patients treated with single-agent capecitabine using slides prepared in Norway. All cohorts included only patients with resectable tumours, and a formalin-fixed, paraffin-embedded tumour tissue block available for analysis. The primary outcome was cancer-specific survival. 828 patients from four cohorts had a distinct outcome and were used as a training cohort to obtain clear ground truth. 1645 patients had a non-distinct outcome and were used for tuning. The biomarker provided a hazard ratio for poor versus good prognosis of 3·84 (95% CI 2·72–5·43; p<0·0001) in the primary analysis of the validation cohort, and 3·04 (2·07–4·47; p<0·0001) after adjusting for established prognostic markers significant in univariable analyses of the same cohort, which were pN stage, pT stage, lymphatic invasion, and venous vascular invasion. A clinically useful prognostic marker was developed using deep learning allied to digital scanning of conventional haematoxylin and eosin stained tumour tissue sections. The assay has been extensively evaluated in large, independent patient populations, correlates with and outperforms established molecular and morphological prognostic markers, and gives consistent results across tumour and nodal stage. The biomarker stratified stage II and III patients into sufficiently distinct prognostic groups that potentially could be used to guide selection of adjuvant treatment by avoiding therapy in very low risk groups and identifying patients who would benefit from more intensive treatment regimes. The Research Council of Norway.

The mitotic checkpoint protein BUB3, cyclin B1 (CCNB1) and pituitary tumor-transforming 1 (PTTG1) regulates cell division, and are sparsely studied in prostate cancer. Deregulation of these genes can lead to genomic instability, a characteristic of more aggressive tumors. We aimed to determine the expression levels of BUB3, CCNB1, and PTTG1 as potential prognostic markers of recurrence after radical prostatectomy. Protein levels were determined by immunohistochemistry on three formalin-fixed paraffin-embedded tissue sections from each of the 253 patients treated with radical prostatectomy. Immunohistochemistry scores were obtained by automated image analysis for CCNB1 and PTTG1. Recurrence, defined as locoregional recurrence, distant metastasis or death from prostate cancer, was used as endpoint for survival analysis. Tumors having both positive and negative tumor areas for cytoplasmic BUB3 (30%), CCNB1 (28%), or PTTG1 (35%) were considered heterogeneous. Patients with ≥1 positive tumor area had significantly increased risk of disease recurrence in univariable analysis compared with patients where all tumor areas were negative for cytoplasmic BUB3 (hazard ratio [HR] = 2.18, 95% confidence interval [CI] 1.41–3.36), CCNB1 (HR = 2.98, 95% CI 1.93–4.61) and PTTG1 (HR = 1.91, 95% CI 1.23–2.97). Combining the scores of cytoplasmic BUB3 and CCNB1 improved risk stratification when integrated with the Cancer of the Prostate Risk Assessment post-Surgical (CAPRA-S) score (difference in concordance index = 0.024, 95% CI 0.001–0.05). In analysis of multiple tumor areas, prognostic value was observed for cytoplasmic BUB3, CCNB1, and PTTG1.

Unfolded protein response (UPR) is a central stress response pathway that is hijacked by tumor cells for their survival. Here, we find that IRE1α signaling, one of the canonical UPR arms, is increased in prostate cancer (PCa) patient tumors. Genetic or small molecule inhibition of IRE1α in syngeneic mouse PCa models and an orthotopic model decreases tumor growth. IRE1α ablation in cancer cells potentiates interferon responses and activates immune system related pathways in the tumor microenvironment (TME). Single-cell RNA-sequencing analysis reveals that targeting IRE1α in cancer cells reduces tumor-associated macrophage abundance. Consistently, the small molecule IRE1α inhibitor MKC8866, currently in clinical trials, reprograms the TME and enhances anti-PD-1 therapy. Our findings show that IRE1α signaling not only promotes cancer cell growth and survival but also interferes with anti-tumor immunity in the TME. Thus, targeting IRE1α can be a promising approach for improving anti-PD-1 immunotherapy in PCa. The IRE1α-XBP1s pathway has been implicated in the regulation of anti-tumor immunity. Here the authors show that IRE1α is increased in prostate cancer (PCa) and that its inhibition reprograms the tumor microenvironment, promoting anti-tumor immune responses in PCa preclinical models.

Chromatin organisation affects gene expression and regional mutation frequencies and contributes to carcinogenesis. Aberrant organisation of DNA has been correlated with cancer prognosis in analyses of the chromatin component of tumour cell nuclei using image texture analysis. As yet, the methodology has not been sufficiently validated to permit its clinical application. We aimed to define and validate a novel prognostic biomarker for the automatic detection of heterogeneous chromatin organisation. Machine learning algorithms analysed the chromatin organisation in 461 000 images of tumour cell nuclei stained for DNA from 390 patients (discovery cohort) treated for stage I or II colorectal cancer at the Aker University Hospital (Oslo, Norway). The resulting marker of chromatin heterogeneity, termed Nucleotyping, was subsequently independently validated in six patient cohorts: 442 patients with stage I or II colorectal cancer in the Gloucester Colorectal Cancer Study (UK); 391 patients with stage II colorectal cancer in the QUASAR 2 trial; 246 patients with stage I ovarian carcinoma; 354 patients with uterine sarcoma; 307 patients with prostate carcinoma; and 791 patients with endometrial carcinoma. The primary outcome was cancer-specific survival. In all patient cohorts, patients with chromatin heterogeneous tumours had worse cancer-specific survival than patients with chromatin homogeneous tumours (univariable analysis hazard ratio [HR] 1·7, 95% CI 1·2–2·5, in the discovery cohort; 1·8, 1·0–3·0, in the Gloucester validation cohort; 2·2, 1·1–4·5, in the QUASAR 2 validation cohort; 3·1, 1·9–5·0, in the ovarian carcinoma cohort; 2·5, 1·8–3·4, in the uterine sarcoma cohort; 2·3, 1·2–4·6, in the prostate carcinoma cohort; and 4·3, 2·8–6·8, in the endometrial carcinoma cohort). After adjusting for established prognostic patient characteristics in multivariable analyses, Nucleotyping was prognostic in all cohorts except for the prostate carcinoma cohort (HR 1·7, 95% CI 1·1–2·5, in the discovery cohort; 1·9, 1·1–3·2, in the Gloucester validation cohort; 2·6, 1·2–5·6, in the QUASAR 2 cohort; 1·8, 1·1–3·0, for ovarian carcinoma; 1·6, 1·0–2·4, for uterine sarcoma; 1·43, 0·68–2·99, for prostate carcinoma; and 1·9, 1·1–3·1, for endometrial carcinoma). Chromatin heterogeneity was a significant predictor of cancer-specific survival in microsatellite unstable (HR 2·9, 95% CI 1·0–8·4) and microsatellite stable (1·8, 1·2–2·7) stage II colorectal cancer, but microsatellite instability was not a significant predictor of outcome in chromatin homogeneous (1·3, 0·7–2·4) or chromatin heterogeneous (0·8, 0·3–2·0) stage II colorectal cancer. The consistent prognostic prediction of Nucleotyping in different biological and technical circumstances suggests that the marker of chromatin heterogeneity can be reliably assessed in routine clinical practice and could be used to objectively assist decision making in a range of clinical settings. An immediate application would be to identify high-risk patients with stage II colorectal cancer who might have greater absolute benefit from adjuvant chemotherapy. Clinical trials are warranted to evaluate the survival benefit and cost-effectiveness of using Nucleotyping to guide treatment decisions in multiple clinical settings. The Research Council of Norway, the South-Eastern Norway Regional Health Authority, the National Institute for Health Research, and the Wellcome Trust.

BackgroundEmergency medical care, including prehospital treatment, forms an important component of any healthcare system. Like most low-middle-income countries, Nepal has an emergency medical system that can be described as underdeveloped. Emergency physicians navigating this system may experience challenges or barriers in their treatment of patients. This study aimed to investigate physicians’ perspectives on emergency and prehospital patient management in a low-income country, Nepal, and to understand the challenges and barriers they perceive in emergency treatment including both the prehospital treatment and the immediate in-hospital treatment at the emergency department.MethodsUsing a qualitative study, eight semi-structured interviews with physicians working in a Nepalese emergency department were performed. The interviews were conducted between September and November 2021 and were audio-recorded and transcribed verbatim. Data were subsequently analyzed using the systematic text condensation method.ResultsFour main themes and associated sub-themes were identified: (1) patients’ sociocultural, educational, and financial factors (such as financial issues and financial inequality) and regional differences; (2) emergency department’s organization and resources concerning human and material resources, protocols, and guidelines; (3) problems with the emergency department (ED) service’s qualities and availability caused by an insufficient integration of the ED and the EMS, prehospital resources, and financial interests in the EMS; and (4) surrounding healthcare system’s impact on the ED where, especially, the levels of organized primary care, governmental responsibilities, and healthcare structure were addressed.ConclusionsThe physicians identified numerous regularly encountered challenges and barriers. These challenges stretched beyond the ED and into various aspects of society. The patients’ financial problems were described as the greatest problem, restricting the treatment due to a given patient’s inability or unwillingness to pay for the required procedures. The physicians were thus restricted in completing their duties to the desired levels. The low quality of prehospital care and a lack of education and awareness of common diseases and symptoms in a significant proportion of patients were identified by many participants as being significant issues. The aforementioned challenges or barriers directly resulted in patients arriving in critical conditions that could have been avoided if the disease were treated earlier.

Deep learning is expected to aid pathologists in tasks such as tumour segmentation. We developed a general tumour segmentation model for histopathological images and examined its performance in different cancer types. The model was developed using over 20,000 whole-slide images from over 4000 patients with colorectal, endometrial, lung, or prostate carcinoma. Performance was validated in pre-planned analyses on external cohorts with over 3000 patients across six cancer types. Exploratory analyses included over 1500 additional patients from The Cancer Genome Atlas. Average Dice coefficient was over 80% in all validation cohorts with en bloc resection specimens and in The Cancer Genome Atlas cohorts. No performance loss was observed when comparing the general model with single-cancer models specialised in cancer types from the development set. In conclusion, extensive and rigorous evaluations demonstrate that generic tumour segmentation by a single model is possible across cancer types, patient populations, sample preparations and slide scanners.

Key Points Academic interest in the role of chromosomal instability (CIN) in cancer development and the influence of the resultant large-scale genomic alterations on clinical outcomes is increasing Aneuploidy — that is, the presence of an abnormal amount of cellular DNA, is an inevitable result of CIN, and this characteristic can be detected and quantified using DNA cytometry DNA ploidy (cellular DNA quantity) is an independent prognostic marker in patients with node-negative invasive breast, early stage endometrioid endometrial, early stage ovarian, prostate, or colorectal cancers In patients with Barrett oesophagus, DNA ploidy can be combined with other biomarkers to identify disease that will progress to high-grade dysplasia and/or carcinoma, and to improve the diagnostic sensitivity of pulmonary cytology In cervical screening tests, detection of aneuploid cells in Pap smears or using liquid-based cytology is a reliable, cost-effective indicator of the early stages of neoplastic progression toward squamous-cell carcinoma Chromosome instability (CIN) is gaining increasing interest as a central process in cancer, and is indicated whenever tumour cells harbour an abnormal quantity of DNA, termed 'aneuploidy'. In this Review, the authors review the literature published since 2000 that support the hypothesis that aneuploidy is a predictor of a poor prognosis in patients with cancer, focusing on the evidence from studies of seven common epithelial cancer types that performed multivariate analyses. The implications of ploidy analysis with regard to our theoretical understanding of the role of CIN in carcinogenesis, as well as its prognostic use in the clinic, are discussed. Chromosome instability (CIN) is gaining increasing interest as a central process in cancer. CIN, either past or present, is indicated whenever tumour cells harbour an abnormal quantity of DNA, termed 'aneuploidy'. At present, the most widely used approach to detecting aneuploidy is DNA cytometry — a well-known research assay that involves staining of DNA in the nuclei of cells from a tissue sample, followed by analysis using quantitative flow cytometry or microscopic imaging. Aneuploidy in cancer tissue has been implicated as a predictor of a poor prognosis. In this Review, we have explored this hypothesis by surveying the current landscape of peer-reviewed research in which DNA cytometry has been applied in studies with disease-appropriate clinical follow up. This area of research is broad, however, and we restricted our survey to results published since 2000 relating to seven common epithelial cancers (those of the breast; endometrium, ovary, and uterine cervix; oesophagus; colon and rectum; lung; prostate; and bladder). We placed particular emphasis on results from multivariate analyses to pinpoint situations in which the prognostic value of aneuploidy as a biomarker is strong compared with that of existing indicators, such as clinical stage, histological grade, and specific molecular markers. We summarize the implications of our findings for the prognostic use of ploidy analysis in the clinic and for the theoretical understanding of the role of CIN in carcinogenesis.

Background: The high degree of genomic diversity in cancer represents a challenge for identifying objective prognostic markers. We aimed to examine the extent of tumour heterogeneity and its effect on the evaluation of a selected prognostic marker using prostate cancer as a model. Methods: We assessed Gleason Score (GS), DNA ploidy status and phosphatase and tensin homologue (PTEN) expression in radical prostatectomy specimens (RP) from 304 patients followed for a median of 10 years (interquartile range 6–12). GS was assessed for every tumour-containing block and DNA ploidy for a median of four samples for each RP. In a subgroup of 40 patients we assessed DNA ploidy and PTEN status in every tumour-containing block. In 102 patients assigned to active surveillance (AS), GS and DNA ploidy were studied in needle biopsies. Results: Extensive heterogeneity was observed for GS (89% of the patients) and DNA ploidy (40% of the patients) in the cohort, and DNA ploidy (60% of the patients) and PTEN expression (75% of the patients) in the subgroup. DNA ploidy was a significant prognostic marker when heterogeneity was taken into consideration. In the AS cohort we found heterogeneity in GS (24%) and in DNA ploidy (25%) specimens. Conclusions: Multi-sample analysis should be performed to support clinical treatment decisions.

Background BRCA1 gene inactivation causes chromosomal instability, leading to rapid accumulation of chromosomal rearrangements and mutations. The loss of BRCA1 function due to either germline/somatic mutation or epigenetic silencing is observed in most high-grade serous carcinomas of the ovary. Methods DNA ploidy and gene expression profile were used in order to compare gross genomic alteration and gene expression pattern between cases with BRCA1 loss through mutation, BRCA1 epigenetic loss, and no BRCA1 loss in cases of high-grade serous carcinoma with known BRCA1 and BRCA 2 status. Results Using image cytometry and oligonucleotide microarrays, we analyzed DNA ploidy, S-phase fraction and gene expression profile of 28 consecutive cases of ovarian high-grade serous adenocarcinomas, which included 8 tumor samples with BRCA1 somatic or germline mutation, 9 samples with promoter hypermethylation of BRCA1, and 11 samples with no BRCA1 loss. None had BRCA2 mutations. The prevalence of aneuploidy and tetraploidy was not statistically different in the three groups with different BRCA1 status. The gene expression profiles were also very similar between the groups, with only two genes showing significant differential expression when comparison was made between the group with BRCA1 mutation and the group with no demonstrable BRCA1 loss. There were no genes showing significant differences in expression when the group with BRCA1 loss through epigenetic silencing was compared to either of the other two groups. Conclusions In this series of 28 high-grade serous carcinomas, gross genomic alteration characterized by aneuploidy did not correlate with BRCA1 status. In addition, the gene expression profiles of the tumors showed negligible differences between the three defined groups based on BRCA1 status. This suggests that all ovarian high-grade serous carcinomas arise through oncogenic mechanisms that result in chromosomal instability, irrespective of BRCA status; the molecular abnormalities underlying this in the BRCA intact tumors remains unknown.

Cancer cells exploit many of the cellular adaptive responses to support their survival needs. One such critical pathway in eukaryotic cells is the unfolded protein response (UPR) that is important in normal physiology as well as disease states, including cancer. Since UPR can serve as a lever between survival and death, regulated control of its activity is critical for tumor formation and growth although the underlying mechanisms are poorly understood. Here we show that one of the main transcriptional effectors of UPR, activating transcription factor 4 (ATF4), is essential for prostate cancer (PCa) growth and survival. Using systemic unbiased gene expression and proteomic analyses, we identified a novel direct ATF4 target gene, family with sequence similarity 129 member A (FAM129A), which is critical in mediating ATF4 effects on prostate tumorigenesis. Interestingly, FAM129A regulated both PERK and eIF2α in a feedback loop that differentially channeled the UPR output. ATF4 and FAM129A protein expression is increased in patient PCa samples compared with benign prostate. Importantly, in vivo therapeutic silencing of ATF4-FAM129A axis profoundly inhibited tumor growth in a preclinical PCa model. These data support that one of the canonical UPR branches, through ATF4 and its target gene FAM129A, is required for PCa growth and thus may serve as a novel therapeutic target.