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The current standard-of-care adjuvant treatment for patients with colorectal cancer (CRC) comprises a fluoropyrimidine (5-fluorouracil or capecitabine) as a single agent or in combination with oxaliplatin, for either 3 or 6 months. Selection of therapy depends on conventional histopathological staging procedures, which constitute a blunt tool for patient stratification. Given the relatively marginal survival benefits that patients can derive from adjuvant treatment, improving the safety of chemotherapy regimens and identifying patients most likely to benefit from them is an area of unmet need. Patient stratification should enable distinguishing those at low risk of recurrence and a high chance of cure by surgery from those at higher risk of recurrence who would derive greater absolute benefits from chemotherapy. To this end, genetic analyses have led to the discovery of germline determinants of toxicity from fluoropyrimidines, the identification of patients at high risk of life-threatening toxicity, and enabling dose modulation to improve safety. Thus far, results from analyses of resected tissue to identify mutational or transcriptomic signatures with value as prognostic biomarkers have been rather disappointing. In the past few years, the application of artificial intelligence-driven models to digital images of resected tissue has identified potentially useful algorithms that stratify patients into distinct prognostic groups. Similarly, liquid biopsy approaches involving measurements of circulating tumour DNA after surgery are additionally useful tools to identify patients at high and low risk of tumour recurrence. In this Perspective, we provide an overview of the current landscape of adjuvant therapy for patients with CRC and discuss how new technologies will enable better personalization of therapy in this setting.

The number of publications on deep learning for cancer diagnostics is rapidly increasing, and systems are frequently claimed to perform comparable with or better than clinicians. However, few systems have yet demonstrated real-world medical utility. In this Perspective, we discuss reasons for the moderate progress and describe remedies designed to facilitate transition to the clinic. Recent, presumably influential, deep learning studies in cancer diagnostics, of which the vast majority used images as input to the system, are evaluated to reveal the status of the field. By manipulating real data, we then exemplify that much and varied training data facilitate the generalizability of neural networks and thus the ability to use them clinically. To reduce the risk of biased performance estimation of deep learning systems, we advocate evaluation in external cohorts and strongly advise that the planned analyses, including a predefined primary analysis, are described in a protocol preferentially stored in an online repository. Recommended protocol items should be established for the field, and we present our suggestions.

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.

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.

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.

Overtreatment is a major concern in men diagnosed with prostate cancer. The aim of this study was to evaluate the combined prognostic role of three frequent molecular alterations in prostate cancer, namely relative 8q gain, ERG overexpression, and loss of PTEN expression, in a series of 136 patients with prostate cancer treated with prostatectomy and with a long follow-up. Fluorescent in situhybridization was used to detect the relative copy number of 8q and immunohistochemistry was used for quantitative assessment of ERG and PTEN expression. During a median follow-up period of 117.8 months, 66 (49%) patients had disease recurrence. Relative 8q gain, ERG overexpression, and loss of PTEN expression were observed in 18%, 56%, and 33% of the cases, respectively. No association with patient recurrence-free survival was found for relative 8q gain or ERG overexpression on their own, whereas loss of PTEN expression was associated with worse recurrence-free survival (P=.006). Interestingly, in the subgroup of patients with normal PTEN expression, we found that the combined relative 8q gain/ERG overexpression is associated with high risk of recurrence (P=.008), suggesting that alternative mechanisms exist for progression into clinically aggressive disease. Additionally, in intermediate-risk patients with normal PTEN expression in their tumors, the combination of 8q gain/ERG overexpression was associated with a poor recurrence-free survival (P<.001), thus indicating independent prognostic value. This study shows that the combined analysis of 8q, ERG and PTEN contributes to an improved clinical outcome stratification of prostate cancer patients treated with radical prostatectomy.

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 increasingAneuploidy — 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 cytometryDNA 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 cancersIn 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 cytologyIn 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

DNA ploidy analysis is a useful tool to distinguish the partial hydatidiform moles (PMs) from complete hydatidiform moles (CMs) and nonmolar abortuses (NAs). DNA ploidy histograms of hydatidiform moles are sometimes difficult to interpret because of the uneven distribution of nuclei in the S-phase, simulating aneuploid peaks. In this study, we analyzed DNA ploidy histograms of 25 CMs, 16 PMs, and 28 NAs, with special reference to the accumulation of cells in the late S-phase using a high-resolution DNA image cytometry. All the gestational products demonstrated the accumulation of cells in the late part of the S-phase fraction. To objectify the observation, we compared the percentage of cells in the second quarter with that of the third quarter of the S-phase fraction. All the gestational products had significantly lower (P< 0.001) percentage of cells in the second compared with that of the third quarter of the S-phase. The mean ratios of the third quarter to the second quarter in CMs, PMs, and NAs were 1.9, 1.7, and 2.5, respectively. This was significantly different from that of highly proliferative endometrial carcinomas. The knowledge of this specific S-phase fraction distribution in molar and nonmolar pregnancy material is important when interpreting the DNA histograms. The possibility of hypoxia being the cause of this phenomenon is also discussed.

Background: In the majority of colorectal carcinomas, both copies of the tumor suppressor gene TP53 (tumor protein 53) are known to be inactivated. In contrast to a loss of tumor suppressor function, it has been suggested that an increased copy number of the RBI gene is involved in the progression of these tumors. Purpose: To determine genetic alterations at chromosomes 13 and 17 in colorectal tumors, we have studied several loci on these chromosomes, with special focus on the RBI and TP53 genes at both the level of DNA sequence and the level of gene expression. Methods: Restriction fragment length polymorphism analysis was performed after alkaline Southern blotting of the DNA fragments and hybridization (in 7% sodium dodecyl sulfate and 0.5 M NaPO4 of the nylon membranes with multi-primed, radioactively labeled probes. Total RNA was extracted from tissue biopsy specimens by homogenization of the samples in guanidinium thiocyanate followed by separation in a CsCl gradient. By use of an image-processing system, x-ray film signals were measured densitometrically. Point mutations within the TP53 gene were detected by use of polymerase chain reaction (PCR) in combination with constant denaturant gel electrophoresis. Direct sequencing of PCR products revealed the exact nature of the mutations. Protein expression of TP53 was seen by immuno-staining of sections from paraffin-embedded material using a mouse monoclonal antibody. The two-sided Fisher‘s Exact Test was used for statistical analysis. Results: An increase in allelic copy number at 13q loci was seen in 10 (32% of 31 tumors. In the majority of the cases, this increase probably reflected a change in the diploid status of chromosome 13; in some cases, however, only part of the 13q seemed to be involved. The RBI gene showed an elevated level of RNA compared with the β-actin signal. Four-teen (48%) of 29 tumors showed loss of heterozygosity at loci on 17p, and base mutations within the TP53 gene were seen in 14 (42% of 33 tumors. RNA and protein analyses of TP53 revealed an increased level of expression in the tumors compared with normal mucosa. Allelic variations seen at 13q and 17p were not associated (P = .7). Conclusions: Our results suggest that, in addition to aneuploidy, gain of specific chromosome 13 sequences is involved in the tumorigenesis of the colon and rectum. In addition, they confirm the importance of TP53 mutations for the progression of such tumors and support the view that accumulation of events is more important than the order of events. The genetic changes observed at chromosome arms 13q and 17p seem to be independent of each other. [J Natl Cancer Inst 84:1100–1108, 1992]