Prognostic impact of the IASLC grading system of lung adenocarcinoma: a systematic review and meta-analysis.

AIMS: Tumour grading is an essential part of the pathologic assessment that promotes patient management. The International Association for the Study of Lung Cancer (IASLC) proposed a grading system for non-mucinous lung adenocarcinoma in 2020. We aimed to validate the prognostic impact of this novel grading system on overall survival (OS) and recurrence-free survival (RFS) based on literature data. METHODS AND RESULTS: The review protocol was registered in PROSPERO (CRD42023396059). We aimed to identify randomized or non-randomized controlled trials published after 2020 comparing different IASLC grade categories in Medline, Embase, and CENTRAL. Hazard ratios (HRs) with 95% confidence intervals (CIs) of OS and RFS were pooled and the Quality In Prognosis Studies (QUIPS) tool was used to assess the risk of bias in the included studies. Ten articles were eligible for this review. Regarding OS estimates, grade 1 lung adenocarcinomas were better than grade 3 both in univariate and multivariate analyses (HROSuni = 0.19, 95% CI: 0.05-0.66, p = 0.009; HROSmulti = 0.21, 95% CI: 0.12-0.38, p < 0.001). Regarding RFS estimates, grade 3 adenocarcinomas had a worse prognosis than grade 1 in multivariate analysis (HRRFSmulti: 0.22, 95% CI: 0.14-0.35, p < 0.001). CONCLUSION: The literature data and the result of our meta-analysis demonstrate the prognostic relevance of the IASLC grading system. This supports the inclusion of this prognostic parameter in daily routine worldwide.

Real-world applications of the new grading system in lung adenocarcinoma: A study of 907 patients focusing on revealing the relationship between pathologic grade and genetic status.

BACKGROUND: The status of the lung adenocarcinoma (LUAD) grading system and the association between LUAD differentiation, driver genes, and clinicopathological features remain to be elucidated. METHODS: We included patients with invasive non-mucinous LUAD, evaluated their differentiation, and collected available clinicopathological information, gene mutations, and analyzed clinical outcomes. RESULTS: Among the 907 patients with invasive non-mucinous LUAD, 321 (35.4 %) were poorly differentiated, 422 (46.5 %) were moderately differentiated, and 164 (18.1 %) were well differentiated. EGFR mutation was more common in the LUADs accompanied without CGP (complex glandular pattern) than LUADs with CGP (p < 0.001). Correlation analysis between mutations and clinical characteristics showed that EGFR gene mutation (p < 0.001), KRAS gene mutation (p < 0.05), and ALK gene rearrangement (p < 0.001) were significantly related to the degree of tumor differentiation, and the KRAS and ALK gene mutation frequencies were higher in the low-differentiation group than in the high and medium differentiation groups. The EGFR mutation frequency was higher in the well/moderately differentiated adenocarcinoma group. CONCLUSIONS: Our study adds to the evidence regarding the role of the grading system in prognosis. EGFR, KRAS, and ALK are related to the degree of tumor differentiation.

Digital image analysis of Ki67 hotspot detection and index counting in gastroenteropancreatic neuroendocrine neoplasms.

The Ki-67 proliferative index plays a pivotal role in the subclassification of neuroendocrine neoplasm (NEN) according to the WHO Classification of Digestive System Tumors (5th edition), which designates neuroendocrine tumor (NET) grades 1, 2, and 3 for Ki-67 proliferative index of <3 %, 3-20 %, and >20 %, respectively. Proliferative index calculation must be performed in the hotspot, traditionally selected by visual scanning at low-power magnification. Recently, gradient map visualization has emerged as a tool for various purposes, including hotspot selection. This study includes 97 cases of gastrointestinal neuroendocrine neoplasms, with hotspots selected by bare eye and gradient map visualization (GM). Each hotspot was analyzed using three methods: eye estimation (EE), digital image analysis (DIA), and manual counting. Of the NENs studied, 91 % were NETs (26 % for G1, 55 % for G2, and 10 % for G3). Only 9 cases were neuroendocrine carcinoma (NEC). Between two hotspot selection methods, GM resulted in a higher grade in 14.77 % of cases, primarily upgrading from NET G1 to G2. Among the counting methods, DIA demonstrated substantial agreement with manual counting, both for pathologist and resident. Grading by other methods tended to result in a higher grade than MC (26.99 % with EE and 8.52 % with DIA). Given its clinical and statistical significance, this study advocates for the application of GM in hotspot selection to identify higher-grade tumors. Furthermore, DIA provides accurate grading, offering time efficiency over MC.

Study on an Automatic Classification Method for Determining the Malignancy Grade of Glioma Pathological Sections Based on Hyperspectral Multi-Scale Spatial-Spectral Fusion Features.

This study describes a novel method for grading pathological sections of gliomas. Our own integrated hyperspectral imaging system was employed to characterize 270 bands of cancerous tissue samples from microarray slides of gliomas. These samples were then classified according to the guidelines developed by the World Health Organization, which define the subtypes and grades of diffuse gliomas. We explored a hyperspectral feature extraction model called SMLMER-ResNet using microscopic hyperspectral images of brain gliomas of different malignancy grades. The model combines the channel attention mechanism and multi-scale image features to automatically learn the pathological organization of gliomas and obtain hierarchical feature representations, effectively removing the interference of redundant information. It also completes multi-modal, multi-scale spatial-spectral feature extraction to improve the automatic classification of glioma subtypes. The proposed classification method demonstrated high average classification accuracy (>97.3%) and a Kappa coefficient (0.954), indicating its effectiveness in improving the automatic classification of hyperspectral gliomas. The method is readily applicable in a wide range of clinical settings, offering valuable assistance in alleviating the workload of clinical pathologists. Furthermore, the study contributes to the development of more personalized and refined treatment plans, as well as subsequent follow-up and treatment adjustment, by providing physicians with insights into the underlying pathological organization of gliomas.

Grading Challenges and Prognostic Insights in Chromophobe Renal Cell Carcinoma: A Retrospective Study of 72 Patients.

Chromophobe RCC (ChRCC) carries the best prognosis among all RCC subtypes, yet it lacks a proper grading system. Various systems have been suggested in the past, causing much controversy, and Avulova et al. recently proposed a promising four-tier grading system that takes into consideration tumor necrosis. Dysregulation of the mammalian target of the rapamycin (mTOR) pathway plays a key role in ChRCC pathogenesis, highlighting its molecular complexity. The present retrospective study aimed to evaluate the prognostic factors associated with a more aggressive ChRCC phenotype. Materials and Methods: Seventy-two patients diagnosed with ChRCC between 2004 and 2017 were included in our study. Pathology reports and tissue blocks were reviewed, and immunohistochemistry (IHC) was performed in order to assess the expressions of CYLD (tumor-suppressor gene) and mTOR, among other markers. Univariate analysis was performed, and OS was assessed using the Kaplan-Meier method. Results: In our study, 74% of patients were male, with a mean age of 60 years, and the mean tumor size was 63 mm (±44). The majority (54%) were followed for more than 10 years at intervals ranging between 44 and 222 months. The risk of death was significantly higher for patients that were classified as Grade 4 in the Avulova system (HR: 5.83; 95% CI, 1.37-24.7; p: = 0.017). As far as the IHC is concerned, mTOR expression was associated with an HR of 8.57 (95% CI, 1.91-38.5; p = 0.005), and CYLD expression was associated with an HR of 17.3 (95% CI, 1.57-192; p = 0.02). Conclusions: In our study, the Avulova grading system seems to be positively correlated with OS in patients diagnosed with ChRCC. Furthermore, an elevated mTOR expression also shows a negative correlation with OS, whereas an elevated CYLD expression does not seem to exert a protective role. However, because only a small proportion (4.2%) of our patients died due to ChRCC, despite the long follow-up period, the results must be interpreted with caution. Further research is needed to validate our findings.

Concordance of biopsy and pathologic ISUP grading in salvage radical prostatectomy patients for recurrent prostate cancer.

PURPOSE: To investigate the concordance of biopsy and pathologic International Society of Urological Pathology (ISUP) grading in salvage radical prostatectomy (SRP) patients for recurrent prostate cancer. METHODS: Within a high-volume center database, we identified patients who underwent SRP for recurrent prostate cancer (PCa) between 2004 and 2020. Upgrading, downgrading, concordance, and any discordance between posttreatment biopsy ISUP and ISUP at SRP were tested. Logistic regression models were used to predict ISUP upgrading and ISUP discordance. Models were adjusted for prostatic specific antigen before SRP, age at surgery, initial prostatic specific antigen (PSA), type of primary treatment, time from primary PCa diagnosis to SRP, number of positive cores at biopsy, and original Gleason score. RESULTS: Overall, 184 patients with available biopsy and pathologic ISUP grading were identified. Of those, 17.4% (n = 32), 40.8% (n = 75), 19.6% (n = 36), and 22.2% (n = 41) harbored biopsy ISUP 1, ISUP 2, ISUP 3, and ISUP 4-5 grading, respectively. Pathologic ISUP 1, ISUP 2, ISUP 3, and ISUP 4-5 grading was recorded in 6.0% (n = 11), 40.8% (n = 75), 32.1% (n = 59), and 21.2% (n = 39), respectively. Median PSA before SRP was 5.5 ng/ml (interquartile range [IQR]: 3.1-8.1 ng/ml), median age at SRP was 65.1 years (IQR:60.7-69.4 years) and median time from original PCa diagnosis to SRP was 47 months (IQR: 27.3-85.2 months). Concordance of biopsy and pathologic ISUP was identified in 45.1% (n = 83). Conversely, any ISUP discordance, upgrading and downgrading of at least one ISUP group was identified in 54.9% (n = 101), 35.3% (n = 65), and 19.6% (n = 36). In logistic models, none of the preoperative characteristics was associated with upgrading or ISUP discordance (all p > 0.1). CONCLUSION: Discordance between biopsy and pathologic ISUP grading is common at SRP. However, in 45% of SRP cases biopsy ISUP is capable to predict pathologic ISUP. Further studies are necessary to identify characteristics for ISUP upgrading at SRP.

Impact of prostate biopsy secondary pathology review on radiotherapy management.

BACKGROUND: The Gleason scoring system is the most widely used method to assess prostate adenocarcinoma pathology however interobserver variability is significant. Gleason score, PSA level, and clinical stage comprise the NCCN risk stratification that guides treatment decision making. Given the importance of an accurate Gleason score and wide interobserver variability, referral centers routinely review outside pathology at the time of consultation. We sought to address the impact a secondary pathology review had on radiation therapy treatment recommendations in men with prostate cancer at our institution. METHODS: We retrospectively collected patient data on 342 patients seen at our institution from January 2012 to December 2018. Clinicopathologic data were used to subdivide patients into risk groups and available treatment options per NCCN criteria. Cases reviewed by our genitourinary pathologist (GUP) were compared with reports from outside pathologists. Inter-rater reliability between pathologists was assessed with weighted Cohen's kappa statistic and agreement of treatment options was determined by McNemar's exact tests. RESULTS: GUP scored more cores positive in 16.47% of cases on secondary review. Primary Gleason score was changed in 12.28% of patients and secondary score in 26.02% of cases. Total Gleason score was different in 29.24% of cases, 19.01% were downgraded and 10.23% upgraded. The weighted kappa statistic was 0.759 (95% confidence interval [CI]: 0.711, 0.807). 18.77% of patients were assigned to a different NCCN risk group following secondary review. The weighted kappa statistic comparing NCCN risk stratification was 0.802 (95% CI: 0.754, 0.850). Secondary review influenced radiation therapy recommendations pertaining to brachytherapy boost and androgen deprivation therapy in men with high risk disease (χ2 = 5.33, p = 0.0386; χ2 = 8.05, p = 0.0072, respectively). Kappa statistic was found to be highest when GUP assessed high-risk disease versus all other categories (κ = 0.823, 95% CI: 0.750, 0.895). CONCLUSIONS: We found nearly one in five men (18.7%) was assigned a different NCCN risk group and thus offered potentially different treatment options after a secondary pathology review at our institution. Given the inherent nature of prostate cancer and lung disease-specific survival associated with modern therapies, our study demonstrates the importance of a secondary pathology review and its potential impact on radiation therapy recommendations.

Comparative analysis of the value of amide proton transfer-weighted imaging and diffusion kurtosis imaging in evaluating the histological grade of cervical squamous carcinoma.

BACKGROUND: Uterine cervical cancer (UCC) was the fourth leading cause of cancer death among women worldwide. The conventional MRI hardly revealing the microstructure information. This study aimed to compare the value of amide proton transfer-weighted imaging (APTWI) and diffusion kurtosis imaging (DKI) in evaluating the histological grade of cervical squamous carcinoma (CSC) in addition to routine diffusion-weighted imaging (DWI). METHODS: Forty-six patients with CSC underwent pelvic DKI and APTWI. The magnetization transfer ratio asymmetry (MTRasym), apparent diffusion coefficient (ADC), mean diffusivity (MD) and mean kurtosis (MK) were calculated and compared based on the histological grade. Correlation coefficients between each parameter and histological grade were calculated. RESULTS: The MTRasym and MK values of grade 1 (G1) were significantly lower than those of grade 2 (G2), and those parameters of G2 were significantly lower than those of grade 3 (G3). The MD and ADC values of G1 were significantly higher than those of G2, and those of G2 were significantly higher than those of G3. MTRasym and MK were both positively correlated with histological grade (r = 0.789 and 0.743, P <  0.001), while MD and ADC were both negatively correlated with histological grade (r = - 0.732 and - 0.644, P <  0.001). For the diagnosis of G1 and G2 CSCs, AUC (APTWI+DKI + DWI) > AUC (DKI + DWI) > AUC (APTWI+DKI) > AUC (APTWI+DWI) > AUC (MTRasym) > AUC (MK) > AUC (MD) > AUC (ADC), where the differences between AUC (APTWI+DKI + DWI), AUC (DKI + DWI) and AUC (ADC) were significant. For the diagnosis of G2 and G3 CSCs, AUC (APTWI+DKI + DWI) > AUC (APTWI+DWI) > AUC (APTWI+DKI) > AUC (DKI + DWI) > AUC (MTRasym) > AUC (MK) > AUC (MD > AUC (ADC), where the differences between AUC (APTWI+DKI + DWI), AUC (APTWI+DWI) and AUC (ADC) were significant. CONCLUSION: Compared with DWI and DKI, APTWI is more effective in identifying the histological grades of CSC. APTWI is recommended as a supplementary scan to routine DWI in CSCs.

Tumour immune landscape of paediatric high-grade gliomas.

Over the past decade, remarkable progress has been made towards elucidating the origin and genomic landscape of childhood high-grade brain tumours. It has become evident that paediatric high-grade gliomas differ from those in adults with respect to multiple defining aspects including: DNA copy number, gene expression profiles, tumour locations within the CNS and genetic alterations such as somatic histone mutations. Despite these advances, clinical trials for children with gliomas have historically been based on ineffective adult regimens that fail to take into consideration the fundamental biological differences between the two. Additionally, although our knowledge of the intrinsic cellular mechanisms driving tumour progression has considerably expanded, little is known about the dynamic tumour immune microenvironment in paediatric high-grade gliomas. In this review, we explore the genetic and epigenetic landscape of these gliomas and how this drives the creation of specific tumour subgroups with meaningful survival outcomes. Further, we provide a comprehensive analysis of the paediatric high-grade glioma tumour immune microenvironment and discuss emerging therapeutic efforts aimed at exploiting the immune functions of these tumours.

Aneuploidy drives lethal progression in prostate cancer.

Aneuploidy, defined as chromosome gains and losses, is a hallmark of cancer. However, compared with other tumor types, extensive aneuploidy is relatively rare in prostate cancer. Thus, whether numerical chromosome aberrations dictate disease progression in prostate cancer patients is not known. Here, we report the development of a method based on whole-transcriptome profiling that allowed us to identify chromosome-arm gains and losses in 333 primary prostate tumors. In two independent cohorts (n = 404) followed prospectively for metastases and prostate cancer-specific death for a median of 15 years, increasing extent of tumor aneuploidy as predicted from the tumor transcriptome was strongly associated with higher risk of lethal disease. The 23% of patients whose tumors had five or more predicted chromosome-arm alterations had 5.3 times higher odds of lethal cancer (95% confidence interval, 2.2 to 13.1) than those with the same Gleason score and no predicted aneuploidy. Aneuploidy was associated with lethality even among men with high-risk Gleason score 8-to-10 tumors. These results point to a key role of aneuploidy in driving aggressive disease in primary prostate cancer.

Quantitative analysis of abnormalities in gynecologic cytopathology with deep learning.

Cervical cancer is one of the most frequent cancers in women worldwide, yet the early detection and treatment of lesions via regular cervical screening have led to a drastic reduction in the mortality rate. However, the routine examination of screening as a regular health checkup of women is characterized as time-consuming and labor-intensive, while there is lack of characteristic phenotypic profile and quantitative analysis. In this research, over the analysis of a privately collected and manually annotated dataset of 130 cytological whole-slide images, the authors proposed a deep-learning diagnostic system to localize, grade, and quantify squamous cell abnormalities. The system can distinguish abnormalities at the morphology level, namely atypical squamous cells of undetermined significance, low-grade squamous intraepithelial lesion, high-grade squamous intraepithelial lesion, and squamous cell carcinoma, as well as differential phenotypes of normal cells. The case study covered 51 positive and 79 negative digital gynecologic cytology slides collected from 2016 to 2018. Our automatic diagnostic system demonstrated its sensitivity of 100% at slide-level abnormality prediction, with the confirmation with three pathologists who performed slide-level diagnosis and training sample annotations. In the cellular-level classification, we yielded an accuracy of 94.5% in the binary classification between normality and abnormality, and the AUC was above 85% for each subtype of epithelial abnormality. Although the final confirmation from pathologists is often a must, empirically, computer-aided methods are capable of the effective extraction, interpretation, and quantification of morphological features, while also making it more objective and reproducible.

Deep learning-based grading of ductal carcinoma in situ in breast histopathology images.

Ductal carcinoma in situ (DCIS) is a non-invasive breast cancer that can progress into invasive ductal carcinoma (IDC). Studies suggest DCIS is often overtreated since a considerable part of DCIS lesions may never progress into IDC. Lower grade lesions have a lower progression speed and risk, possibly allowing treatment de-escalation. However, studies show significant inter-observer variation in DCIS grading. Automated image analysis may provide an objective solution to address high subjectivity of DCIS grading by pathologists. In this study, we developed and evaluated a deep learning-based DCIS grading system. The system was developed using the consensus DCIS grade of three expert observers on a dataset of 1186 DCIS lesions from 59 patients. The inter-observer agreement, measured by quadratic weighted Cohen's kappa, was used to evaluate the system and compare its performance to that of expert observers. We present an analysis of the lesion-level and patient-level inter-observer agreement on an independent test set of 1001 lesions from 50 patients. The deep learning system (dl) achieved on average slightly higher inter-observer agreement to the three observers (o1, o2 and o3) (κo1,dl = 0.81, κo2,dl = 0.53 and κo3,dl = 0.40) than the observers amongst each other (κo1,o2 = 0.58, κo1,o3 = 0.50 and κo2,o3 = 0.42) at the lesion-level. At the patient-level, the deep learning system achieved similar agreement to the observers (κo1,dl = 0.77, κo2,dl = 0.75 and κo3,dl = 0.70) as the observers amongst each other (κo1,o2 = 0.77, κo1,o3 = 0.75 and κo2,o3 = 0.72). The deep learning system better reflected the grading spectrum of DCIS than two of the observers. In conclusion, we developed a deep learning-based DCIS grading system that achieved a performance similar to expert observers. To the best of our knowledge, this is the first automated system for the grading of DCIS that could assist pathologists by providing robust and reproducible second opinions on DCIS grade.

Pathological evaluation of tumor grade for salivary adenoid cystic carcinoma: A proposal of an objective grading system.

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.

Seminal plasma metabolomics reveals lysine and serine dysregulation as unique features distinguishing between prostate cancer tumors of Gleason grades 6 and 7.

BACKGROUND: Prostate cancer (PCa) is a metabolic disease. Most men are diagnosed with low grade indolent disease and differentiating these men from those who have life threatening cancer is a challenging but important clinical dilemma. There are currently limited biomarkers that can distinguish between the indolent Gleason grade 6 and higher-grade disease. Moreover, some individuals initially diagnosed with low grade disease progress to higher grade disease. Currently prostate biopsies are the only reliable methods of stratifying risk, but biopsies can cause significant morbidity, sample only a small portion of the gland and are costly. Therefore, biomarkers distinguishing between indolent and aggressive patterns of PCa are urgently required to minimize biopsy-associated morbidity, prevent over-treatment of indolent PCa and to better stratify patients for appropriate treatment. METHODS: Seminal fluid samples were collected from normal individuals (n = 13) Before infertility treatment and histologically confirmed PCa patients (n = 51). 1 H Nuclear magnetic resonance spectroscopy and orthogonal partial least square discriminant analysis were used to compare the populations. RESULTS: Alterations in amino acids levels, specifically lysine and serine and changes in glycolytic intermediates were the most significant metabolic features associated with differences between healthy controls and PCa and between Gleason grade 6 (GS6) and Gleason grade 7 (GS7) samples. Orthogonal partial least square plots discriminated healthy controls from PCa samples (R 2 = 0.54, Q 2 = 0.31; area under the receiver operating characteristics curve [AUC] = 0.96), and GS6 from GS7 samples (R 2 = 0.62, Q 2 = 0.49; AUC = 0.98) based on lysine and serine content. CONCLUSION: This study suggests that seminal plasma metabolomics profiling of seminal fluid is a promising means of differentiating indolent from aggressive disease. Particularly, lysine and serine levels may be able to differentiate GS6 from GS7 disease.

Does a high Mandard score really define a poor response to chemotherapy in oesophageal adenocarcinoma?

BACKGROUND: A high Mandard score implies a non-response to chemotherapy in oesophageal adenocarcinoma. However, some patients exhibit tumour volume reduction and a nodal response despite a high score. This study examines survival and recurrence patterns in these patients. METHODS: Clinicopathological factors were analysed using multivariable Cox regression assessing time to death and recurrence. Computed tomography-estimated tumour volume change was examined in a subgroup of consecutive patients. RESULTS: Five hundred and fifty-five patients were included. Median survival was 55 months (Mandard 1-3) and 21 months (Mandard 4 and 5). In the Mandard 4 and 5 group (332 patients), comparison between complete nodal responders and persistent nodal disease showed improved survival (90 vs 18 months), recurrence rates (locoregional 14.75 vs 28.74%, systemic 24.59 vs 48.42%) and circumferential resection margin positivity (22.95 vs 68.11%). Complete nodal response independently predicted improved survival (hazard ratio 0.34 (0.16-0.74). Post-chemotherapy tumour volume reduction was greater in patients with a complete nodal response (-16.3 vs -7.7 cm3, p = 0.033) with no significant difference between Mandard groups. CONCLUSION: Patients with a complete nodal response to chemotherapy have significantly improved outcomes despite a poor Mandard score. High Mandard score does not correspond with a non-response to chemotherapy in all cases and patients with nodal downstaging may still benefit from adjuvant chemotherapy.

Baseline correlations and prognostic impact of serum monoclonal proteins in follicular lymphoma.

The presence of a serum monoclonal component has been associated with poor outcomes in some lymphomas. However, data in follicular lymphoma (FL) are scarce. We studied 311 FL patients diagnosed at a single institution, for whom information on serum immunofixation electrophoresis (sIFE) at diagnosis was available. Baseline characteristics and outcomes were compared between patients with a positive (+sIFE) and a negative sIFE (-sIFE). sIFE was positive in 82 patients (26%). Baseline features were comparable between both groups, except for an older age and higher proportion of elevated ß2 -microglobulin levels in the +sIFE group. With a median follow-up of 4.6 years, a +sIFE was associated with a higher risk of early relapse (POD24, 27% vs. 15%, P = 0·02), shorter progression-free survival (PFS; 42% vs. 52% at 5 years, P = 0·008), and shorter overall survival (OS; 59% vs. 77% at 10 years, P = 0·046). In patients >60 years, a +sIFE was an independent predictor of OS [hazard ratio (HR) = 2·4, 95% confidence interval (CI): 1·2-5·0; P = 0·02]. Approximately one quarter of patients with FL has a +sIFE at diagnosis, which is a predictor of poor outcome. These findings encourage further investigation of its relationship with B-cell biology and the tumour microenvironment.

A novel immune-related gene-based prognostic signature to predict biochemical recurrence in patients with prostate cancer after radical prostatectomy.

Accumulating evidences indicates that the immune landscape signature dramatically correlates with tumorigenesis and prognosis of prostate cancer (PCa). Here, we identified a novel immune-related gene-based prognostic signature (IRGPS) to predict biochemical recurrence (BCR) after radical prostatectomy. We also explored the correlation between IRGPS and tumor microenvironment. We identified an IRGPS consisting of seven immune-related genes (PPARGC1A, AKR1C2, COMP, EEF1A2, IRF5, NTM, and TPX2) that were related to the BCR-free survival of PCa patients. The high-risk patients exhibited a higher fraction of regulatory T cells and M2 macrophages than the low-risk BCR patients (P < 0.05) as well as a lower fraction of resting memory CD4 T cells and resting mast cells. These high-risk patients also had higher expression levels of CTLA4, TIGIT, PDCD1, LAG3, and TIM3. Finally, a strong correlation was detected between IRGPS and specific clinicopathological features, including Gleason scores and tumor stage. In conclusion, our study reveals the clinical significance and potential functions of the IRGPS, provides more data for predicting outcomes, and suggests more effective immunotherapeutic target strategies for PCa.

Malignant peritoneal mesothelioma: prognostic significance of clinical and pathologic parameters and validation of a nuclear-grading system in a multi-institutional series of 225 cases.

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.

Automated Detection and Grading of Non-Muscle-Invasive Urothelial Cell Carcinoma of the Bladder.

Accurate grading of non-muscle-invasive urothelial cell carcinoma is of major importance; however, high interobserver variability exists. A fully automated detection and grading network based on deep learning is proposed to enhance reproducibility. A total of 328 transurethral resection specimens from 232 patients were included, and a consensus reading by three specialized pathologists was used. The slides were digitized, and the urothelium was annotated by expert observers. The U-Net-based segmentation network was trained to automatically detect urothelium. This detection was used as input for the classification network. The classification network aimed to grade the tumors according to the World Health Organization grading system adopted in 2004. The automated grading was compared with the consensus and individual grading. The segmentation network resulted in an accurate detection of urothelium. The automated grading shows moderate agreement (κ = 0.48 ± 0.14 SEM) with the consensus reading. The agreement among pathologists ranges between fair (κ = 0.35 ± 0.13 SEM and κ = 0.38 ± 0.11 SEM) and moderate (κ = 0.52 ± 0.13 SEM). The automated classification correctly graded 76% of the low-grade cancers and 71% of the high-grade cancers according to the consensus reading. These results indicate that deep learning can be used for the fully automated detection and grading of urothelial cell carcinoma.

Prognostic grade for resecting hepatocellular carcinoma: multicentre retrospective study.

BACKGROUND: Surgical treatment for hepatocellular carcinoma (HCC) is advancing, but a robust prediction model for survival after resection is not available. The aim of this study was to propose a prognostic grading system for resection of HCC. METHODS: This was a retrospective, multicentre study of patients who underwent first resection of HCC with curative intent between 2000 and 2007. Patients were divided randomly by a cross-validation method into training and validation sets. Prognostic factors were identified using a Cox proportional hazards model. The predictive model was built by decision-tree analysis to define the resection grades, and subsequently validated. RESULTS: A total of 16 931 patients from 795 hospitals were included. In the training set (8465 patients), four surgical grades were classified based on prognosis: grade A1 (1236 patients, 14.6 per cent; single tumour 3 cm or smaller and anatomical R0 resection); grade A2 (3614, 42.7 per cent; single tumour larger than 3 cm, or non-anatomical R0 resection); grade B (2277, 26.9 per cent; multiple tumours, or vascular invasion, and R0 resection); and grade C (1338, 15.8 per cent; multiple tumours with vascular invasion and R0 resection, or R1 resection). Five-year survival rates were 73.9 per cent (hazard ratio (HR) 1.00), 64.7 per cent (HR 1.51, 95 per cent c.i. 1.29 to 1.78), 50.6 per cent (HR 2.53, 2.15 to 2.98), and 34.8 per cent (HR 4.60, 3.90 to 5.42) for grades A1, A2, B, and C respectively. In the validation set (8466 patients), the grades had equivalent reproducibility for both overall and recurrence-free survival (all P < 0.001). CONCLUSION: This grade is used to predict prognosis of patients undergoing resection of HCC.