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Since 1966, when Donald Gleason, MD, first proposed grading prostate cancer based on its histologic architecture, there have been numerous changes in clinical and pathologic practices relating to prostate cancer. Patterns 1 and 2, comprising more than 30% of cases in the original publications by Gleason, are no longer reported on biopsy and are rarely diagnosed on radical prostatectomy. Many of these cases may even have been mimickers of prostate cancer that were described later with the use of contemporary immunohistochemistry. The original Gleason system predated many newly described variants of prostate cancer and our current concept of intraductal carcinoma. Gleason also did not describe how to report prostate cancer on biopsy with multiple cores of cancer or on radical prostatectomy with separate tumor nodules. To address these issues, the International Society of Urological Pathology first made revisions to the grading system in 2005, and subsequently in 2014. Additionally, a new grading system composed of Grade Groups 1 to 5 that was first developed in 2013 at the Johns Hopkins Hospital and subsequently validated in a large multi-institutional and multimodal study was presented at the 2014 International Society of Urological Pathology meeting and accepted both by participating pathologists as well as urologists, oncologists, and radiation therapists. In the present study, we describe updates to the grading of prostate cancer along with the new grading system.

Oral cancer is one of the most common cancers worldwide. Despite easy access to the oral cavity and significant advances in treatment, the morbidity and mortality rates for oral cancer patients are still very high, mainly due to late-stage diagnosis when treatment is less successful. Oral cancer has also been found to be the most expensive cancer to treat in the United States. Early diagnosis of oral cancer can significantly improve patient survival rate and reduce medical costs. There is an urgent unmet need for an accurate and sensitive molecular-based diagnostic tool for early oral cancer detection. Fourier transform infrared spectroscopy has gained increasing attention in cancer research due to its ability to elucidate qualitative and quantitative information of biochemical content and molecular-level structural changes in complex biological systems. The diagnosis of a disease is based on biochemical changes underlying the disease pathology rather than morphological changes of the tissue. It is a versatile method that can work with tissues, cells, or body fluids. In this review article, we aim to summarize the studies of infrared spectroscopy in oral cancer research and detection. It provides early evidence to support the potential application of infrared spectroscopy as a diagnostic tool for oral potentially malignant and malignant lesions. The challenges and opportunities in clinical translation are also discussed.

A recently described nuclear grading system predicted survival in patients with epithelioid malignant pleural mesothelioma. The current study was undertaken to validate the grading system and to identify additional prognostic factors. We analyzed cases of epithelioid malignant pleural mesothelioma from 17 institutions across the globe from 1998 to 2014. Nuclear grade was computed combining nuclear atypia and mitotic count into a grade of I–III using the published system. Nuclear grade was assessed by one pathologist for three institutions, the remaining were scored independently. The presence or absence of necrosis and predominant growth pattern were also evaluated. Two additional scoring systems were evaluated, one combining nuclear grade and necrosis and the other mitotic count and necrosis. Median overall survival was the primary endpoint. A total of 776 cases were identified including 301 (39%) nuclear grade I tumors, 354 (45%) grade II tumors and 121 (16%) grade III tumors. The overall survival was 16 months, and correlated independently with age ( P =0.006), sex (0.015), necrosis (0.030), mitotic count (0.001), nuclear atypia (0.009), nuclear grade (<0.0001), and mitosis and necrosis score (<0.0001). The addition of necrosis to nuclear grade further stratified overall survival, allowing classification of epithelioid malignant pleural mesothelioma into four distinct prognostic groups: nuclear grade I tumors without necrosis (29 months), nuclear grade I tumors with necrosis and grade II tumors without necrosis (16 months), nuclear grade II tumors with necrosis (10 months) and nuclear grade III tumors (8 months). The mitosis–necrosis score stratified patients by survival, but not as well as the combination of necrosis and nuclear grade. This study confirms that nuclear grade predicts survival in epithelioid malignant pleural mesothelioma, identifies necrosis as factor that further stratifies overall survival, and validates the grading system across multiple institutions and among both biopsy and resection specimens. An alternative scoring system, the mitosis–necrosis score is also proposed.

Mucoepidermoid carcinoma (MEC) is the most common carcinoma of the salivary glands. Here, we have used two large patient cohorts with MECs comprising 551 tumors to study clinical, histological, and molecular predictors of survival. One cohort (n = 167), with known CRCT1/3-MAML2 fusion status, was derived from the Hamburg Reference Centre (HRC; graded with the AFIP and Brandwein systems) and the other (n = 384) was derived from the population-based Cancer Registry of North Rhine-Westphalia (LKR-NRW; graded with the AFIP system). The reliability of both the AFIP and Brandwein grading systems was excellent (n = 155). The weighted kappa for inter-rater agreement was 0.81 (95% CI 0.65–0.97) and 0.83 (95% CI 0.71–0.96) for the AFIP and Brandwein systems, respectively. The 5-year relative survival was 79.7% (95% CI 73.2–86.2%). Although the Brandwein system resulted in a higher rate of G3-MECs, survival in G3-tumors (AFIP or Brandwein grading) was markedly worse than in G1/G2-tumors. Survival in > T2 tumors was markedly worse than in those with lower T-stage. Also, fusion-negative MECs had a worse 5-year progression-free survival. The frequency of fusion-positive MECs in the HRC cohort was 78.4%, of which the majority (86.7%) was G1/G2-tumors. In conclusion, the AFIP and Brandwein systems are useful in estimating prognosis and to guide therapy for G3-MECs. However, their significance regarding young age (≤ 30 years) and location-dependent heterogeneity of in particular G2-tumors is more questionable. We conclude that CRTC1/3-MAML2 testing is a useful adjunct to histologic scoring of MECs and for pinpointing tumors with poor prognosis with higher precision, thus avoiding overtreatment.

The International Society of Urological Pathology (ISUP) hosts a reference image database supervised by experts with the purpose of establishing an international standard in prostate cancer grading. Here, we aimed to identify areas of grading difficulties and compare the results with those obtained from an artificial intelligence system trained in grading. In a series of 87 needle biopsies of cancers selected to include problematic cases, experts failed to reach a 2/3 consensus in 41.4% (36/87). Among consensus and non-consensus cases, the weighted kappa was 0.77 (range 0.68–0.84) and 0.50 (range 0.40–0.57), respectively. Among the non-consensus cases, four main causes of disagreement were identified: the distinction between Gleason score 3 + 3 with tangential cutting artifacts vs. Gleason score 3 + 4 with poorly formed or fused glands (13 cases), Gleason score 3 + 4 vs. 4 + 3 (7 cases), Gleason score 4 + 3 vs. 4 + 4 (8 cases) and the identification of a small component of Gleason pattern 5 (6 cases). The AI system obtained a weighted kappa value of 0.53 among the non-consensus cases, placing it as the observer with the sixth best reproducibility out of a total of 24. AI may serve as a decision support and decrease inter-observer variability by its ability to make consistent decisions. The grading of these cancer patterns that best predicts outcome and guides treatment warrants further clinical and genetic studies. Results of such investigations should be used to improve calibration of AI systems.

Three pathological grading systems advocated by Perzin/Szanto, Spiro, and van Weert are currently used for adenoid cystic carcinoma (AdCC). In these systems, the amount or presence of the solid tumor component in AdCC specimens is an important index. However, the “solid tumor component” has not been well defined. Salivary AdCC cases (N = 195) were collected after a central pathology review. We introduced a novel criterion for solid tumor component, minAmax (minor axis maximum). The largest solid tumor nest in each AdCC case was histologically screened, the maximum oval fitting the solid nest was estimated, and the length of the minor axis of the oval (minAmax) was measured. The prognostic cutoff for the minAmax was determined using training and validation cohorts. All cases were evaluated for the four grading systems, and their prognostic impact and interobserver variability were examined. The cutoff value for the minAmax was set at 0.20 mm. Multivariate prognostic analyses showed the minAmax and van Weert systems to be independent prognostic tools for overall, disease‐free, and distant metastasis‐free survival while the Perzin/Szanto and Spiro systems were selected for overall survival but not for disease‐free or distant metastasis‐free survival. The highest hazard ratio for overall survival (11.9) was obtained with the minAmax system. The reproducibility of the minAmax system (kappa coefficient of 0.81) was scored as very good while those of the other three systems were scored as moderate. In conclusion, the minAmax is a simple, objective, and highly reproducible grading system useful for prognostic stratification for salivary AdCC. The amount or presence of the solid tumor component is an important index for histopathological grading of adenoid cystic carcinoma. However, the “solid tumor component” has not been well defined. We introduced a novel objective criterion for solid tumor component, minAmax (minor axis maximum), and showed that the minAmax is a simple, objective, and highly reproducible grading system useful for prognostic stratification for salivary adenoid cystic carcinoma.

Key Points A number of guidelines have been published that include criteria for active surveillance (AS) enrolment and subsequent management to assist clinicians and patients in critically important treatment related decision-making Consensus on inclusion criteria, surveillance schedules and intervention thresholds is currently lacking The future of AS and its uptake as a management modality will depend on better patient selection and validated monitoring schedules to improve identification of disease progression Combining existing evidence and gathering more long-term evidence is needed to derive a broadly supported guideline to reduce variations in clinical practice and to optimize clinical decision-making Active surveillance of men with prostate cancer has received increasing interest over the past decade, resulting in the publication of a wide range of different guidelines on the management of patients in active surveillance programmes, often with very different recommendations. Here, authors describe the various available guidelines and how they differ from each other, highlighting the need for an international consensus on the optimal use of active surveillance in patients with prostate cancer. In the past decade active surveillance (AS) of men with localized prostate cancer has become an increasingly popular management option, and a range of clinical guidelines have been published on this topic. Existing guidelines regarding AS for prostate cancer vary widely, but predominantly state that the most suitable patients for AS are those with pretreatment clinical stage T1c or T2 tumours, serum PSA levels <10 ng/ml, biopsy Gleason scores of 6 or less, a maximum of one or two tumour-positive biopsy core samples and/or a maximum of 50% of cancer per core sample. Following initiation of an AS programme, most guidelines recommend serial serum PSA measurements, digital rectal examinations and surveillance biopsies to check for and identify pathological indications of tumour progression. Definitions of disease reclassification and progression differ among guidelines and multiple criteria for initiation of definitive treatment are proposed. The variety of descriptions of criteria for clinically insignificant prostate cancer indicates a lack of consensus on optimal AS and intervention thresholds. A single set of guidelines are needed in order to reduce variations in clinical practice and to optimize clinical decision-making. To enable truly evidence-based guidelines, further research that combines existing evidence, while also gathering information from more long-term studies is needed.

Malignant peritoneal mesothelioma historically carried a grim prognosis, but outcomes have improved substantially in recent decades. The prognostic significance of clinical, morphologic, and immunophenotypic features remains ill-defined. This multi-institutional cohort comprises 225 malignant peritoneal mesotheliomas, which were assessed for 21 clinical, morphologic, and immunohistochemical parameters. For epithelioid mesotheliomas, combining nuclear pleomorphism and mitotic index yielded a composite nuclear grade, using a previously standardized grading system. Correlation of clinical, morphologic, and immunohistochemical parameters with overall and disease-free survival was examined by univariate and multivariate analyses. On univariate analysis, longer overall survival was significantly associated with diagnosis after 2000 (P = 0.0001), age <60 years (P = 0.0001), ECOG performance status 0 or 1 (P = 0.01), absence of radiographic lymph-node metastasis (P = 0.04), cytoreduction surgery (P < 0.0001), hyperthermic intraperitoneal chemotherapy (P = 0.0001), peritoneal carcinomatosis index <27 (P = 0.01), absence of necrosis (P = 0.007), and epithelioid histotype (P < 0.0001). Among epithelioid malignant mesotheliomas only, longer overall survival was further associated with female sex (P = 0.03), tubulopapillary architecture (P = 0.005), low nuclear pleomorphism (P < 0.0001), low mitotic index (P = 0.0007), and low composite nuclear grade (P < 0.0001). On multivariate analyses, the low composite nuclear grade was independently associated with longer overall and disease-free survival (P < 0.0001). Our data further clarify the interactions of clinical and pathologic features in peritoneal mesothelioma prognosis and validate the prognostic significance of a standardized nuclear-grading system in epithelioid malignant mesothelioma of the peritoneum.

The Ki-67 index is an established prognostic factor in gastrointestinal neuroendocrine tumors (GI-NETs) and defines tumor grade. It is currently estimated by microscopically examining tumor tissue single-immunostained (SS) for Ki-67 and counting the number of Ki-67-positive and Ki-67-negative tumor cells within a subjectively picked hot-spot. Intraobserver variability in this procedure as well as difficulty in distinguishing tumor from non-tumor cells can lead to inaccurate Ki-67 indices and possibly incorrect tumor grades. We introduce two computational tools that utilize Ki-67 and synaptophysin double-immunostained (DS) slides to improve the accuracy of Ki-67 index quantitation in GI-NETs: (1) Synaptophysin-KI-Estimator (SKIE), a pipeline automating Ki-67 index quantitation via whole-slide image (WSI) analysis and (2) deep-SKIE, a deep learner-based approach where a Ki-67 index heatmap is generated throughout the tumor. Ki-67 indices for 50 GI-NETs were quantitated using SKIE and compared with DS slide assessments by three pathologists using a microscope and a fourth pathologist via manually ticking off each cell, the latter of which was deemed the gold standard (GS). Compared to the GS, SKIE achieved a grading accuracy of 90% and substantial agreement (linear-weighted Cohen’s kappa 0.62). Using DS WSIs, deep-SKIE displayed a training, validation, and testing accuracy of 98.4%, 90.9%, and 91.0%, respectively, significantly higher than using SS WSIs. Since DS slides are not standard clinical practice, we also integrated a cycle generative adversarial network into our pipeline to transform SS into DS WSIs. The proposed methods can improve accuracy and potentially save a significant amount of time if implemented into clinical practice.

High Gleason score is currently the best prognostic indicator for poor prognosis in prostate cancer. However, a significant number of patients with low Gleason scores develop aggressive disease as well. In an effort to understand molecular signatures associated with poor outcome in prostate cancer, we analyzed a microarray dataset characterizing 281 prostate cancers from a Swedish watchful-waiting cohort. Patients were classified on the basis of their mRNA microarray signature profiles indicating embryonic stem cell expression patterns (stemness), inactivation of the tumor suppressors p53 and PTEN, activation of several oncogenic pathways, and the TMPRSS2—ERG fusion. Unsupervised clustering identified a subset of tumors manifesting stem-like signatures together with p53 and PTEN inactivation, which had very poor survival outcome, a second group with intermediate survival outcome, characterized by the TMPRSS2—ERG fusion, and three groups with benign outcome. The stratification was validated on a second independent dataset of 150 tumor and metastatic samples from a clinical cohort at Memorial Sloan—Kettering Cancer Center. This classification is independent of Gleason score and therefore provides useful unique molecular profiles for prostate cancer prognosis, helping to predict poor outcome in patients with low or average Gleason scores.