Extranodal extension of lymph node metastasis influences recurrence in prostate cancer: a systematic review and meta-analysis

Deep learning-based whole-body characterization of prostate cancer lesions on [68Ga]Ga-PSMA-11 PET/CT in patients with post-prostatectomy recurrence

PURPOSE

The automatic segmentation and detection of prostate cancer (PC) lesions throughout the body are extremely challenging due to the lesions' complexity and variability in appearance, shape, and location. In this study, we investigated the performance of a three-dimensional (3D) convolutional neural network (CNN) to automatically characterize metastatic lesions throughout the body in a dataset of PC patients with recurrence after radical prostatectomy.

METHODS

We retrospectively collected [68 Ga]Ga-PSMA-11 PET/CT images from 116 patients with metastatic PC at two centers: center 1 provided the data for fivefold cross validation (n = 78) and internal testing (n = 19), and center 2 provided the data for external testing (n = 19). PET and CT data were jointly input into a 3D U-Net to achieve whole-body segmentation and detection of PC lesions. The performance in both the segmentation and the detection of lesions throughout the body was evaluated using established metrics, including the Dice similarity coefficient (DSC) for segmentation and the recall, precision, and F1-score for detection. The correlation and consistency between tumor burdens (PSMA-TV and TL-PSMA) calculated from automatic segmentation and artificial ground truth were assessed by linear regression and Bland‒Altman plots.

RESULTS

On the internal test set, the DSC, precision, recall, and F1-score values were 0.631, 0.961, 0.721, and 0.824, respectively. On the external test set, the corresponding values were 0.596, 0.888, 0.792, and 0.837, respectively. Our approach outperformed previous studies in segmenting and detecting metastatic lesions throughout the body. Tumor burden indicators derived from deep learning and ground truth showed strong correlation (R2 ≥ 0.991, all P < 0.05) and consistency.

CONCLUSION

Our 3D CNN accurately characterizes whole-body tumors in relapsed PC patients; its results are highly consistent with those of manual contouring. This automatic method is expected to improve work efficiency and to aid in the assessment of tumor burden.

Can Machine Learning Models Detect and Predict Lymph Node Involvement in Prostate Cancer? A Comprehensive Systematic Review

(1) Background: Recently, Artificial Intelligence (AI)-based models have been investigated for lymph node involvement (LNI) detection and prediction in Prostate cancer (PCa) patients, in order to reduce surgical risks and improve patient outcomes. This review aims to gather and analyze the few studies available in the literature to examine their initial findings. (2) Methods: Two reviewers conducted independently a search of MEDLINE databases, identifying articles exploring AI's role in PCa LNI. Sixteen studies were selected, and their methodological quality was appraised using the Radiomics Quality Score. (3) Results: AI models in Magnetic Resonance Imaging (MRI)-based studies exhibited comparable LNI prediction accuracy to standard nomograms. Computed Tomography (CT)-based and Positron Emission Tomography (PET)-CT models demonstrated high diagnostic and prognostic results. (4) Conclusions: AI models showed promising results in LN metastasis prediction and detection in PCa patients. Limitations of the reviewed studies encompass retrospective design, non-standardization, manual segmentation, and limited studies and participants. Further research is crucial to enhance AI tools' effectiveness in this area.

Unambiguous radiologic extranodal extension determined by MRI could be a biomarker in predicting metastatic prostate cancer

OBJECTIVE

To explore the relationship between unambiguous radiologic extranodal extension (rENE) and M1 staging in patients with metastatic PCa.

METHODS

A respective analysis of 1073 patients of PCa N1 staging from January 2004 to May 2022 was retrospectively enrolled. They were divided into rENE + and rENE -  groups and retrospectively analyzed the M staging with nuclear medicine data. The correlation index between unambiguous rENE and M1b staging was calculated. Logistic regression was used to evaluate the predictive performance of unambiguous rENE in M1b staging. ROC curves were used to investigate the relationship between unambiguous rENE and M staging in patients who underwent ⁶⁸ Ga-PSMA PET/CT.

RESULTS

A total of 1073 patients were included. Seven hundred and eighty patients were classified into the rENE + group (mean age, 69.6 years ± 8.7 [standard deviation]), and 293 were classified into rENE -  group (mean age, 66.7 years ± 9.4 [standard deviation]). Relationship between unambiguous rENE and M1b existed (r = 0.58, 95%CI: 0.52-0.64, P < 0.05). Unambiguous rENE could be an independent predictor for M1b (OR = 13.64, 95%CI: 9.23-20.14, P < 0.05). The AUC of unambiguous rENE in predicting M1b and M staging was 0.835 and 0.915, respectively, in patients who underwent ⁶⁸ Ga-PSMA PET/CT.

CONCLUSIONS

Unambiguous rENE could be a strong biomarker to predict M1b and M staging in patients with PCa. When rENE came up, patients should perform nuclear medicine immediately, and a systematic treatment should be considered.

The prognostic value of lymph node staging with prostate-specific membrane antigen (PSMA) positron emission tomography/computed tomography (PET/CT) and extended pelvic lymph node dissection in node-positive patients with prostate cancer

OBJECTIVES

To investigate whether patients with suspected pelvic lymph node metastases (molecular imaging [mi] N1) on staging prostate-specific membrane antigen (PSMA) positron emission tomography/computed tomography (PET/CT) had a different oncological outcome compared to those in whom the PSMA PET/CT did not reveal any pelvic lymph node metastases (miN0).

PATIENTS AND METHODS

All patients with pelvic lymph node metastatic (pN1) disease after robot-assisted radical prostatectomy (RARP) and extended pelvic lymph node dissection (ePLND) between January 2017 and December 2020 were included. To assess predictors of biochemical progression of disease after RARP, a multivariable Cox regression analysis was performed, including number of tumour-positive lymph nodes, diameter of the largest nodal metastasis, and extranodal extension.

RESULTS

In total, 145 patients were diagnosed with pN1 disease after ePLND. The median biochemical progression-free survival in patients with miN0 on PSMA PET/CT was 13.7 months, compared to 7.9 months in patients with miN1 disease (P = 0.006). On multivariable Cox regression analysis, both number of tumour-positive lymph nodes (>2 vs 1-2: hazard ratio [HR] 1.97; P = 0.005) and diameter of the largest nodal metastasis (HR 1.12; P < 0.001) were significant independent predictors of biochemical progression of disease.

CONCLUSION

Patients in whom pelvic lymph node metastases were suspected on preoperative PSMA imaging (miN1), patients diagnosed with >2 tumour-positive lymph nodes, and patients with a larger diameter of the largest nodal metastasis had a significantly increased risk of biochemical disease progression after surgery.

Cancer Stemness/Epithelial-Mesenchymal Transition Axis Influences Metastasis and Castration Resistance in Prostate Cancer: Potential Therapeutic Target

Prostate cancer (PCa) is a leading cause of cancer death in men, worldwide. Mortality is highly related to metastasis and hormone resistance, but the molecular underlying mechanisms are poorly understood. We have studied the presence and role of cancer stem cells (CSCs) and the Epithelial-Mesenchymal transition (EMT) in PCa, using both in vitro and in vivo models, thereby providing evidence that the stemness-mesenchymal axis seems to be a critical process related to relapse, metastasis and resistance. These are complex and related processes that involve a cooperative action of different cancer cell subpopulations, in which CSCs and mesenchymal cancer cells (MCCs) would be responsible for invading, colonizing pre-metastatic niches, initiating metastasis and an evading treatments response. Manipulating the stemness-EMT axis genes on the androgen receptor (AR) may shed some light on the effect of this axis on metastasis and castration resistance in PCa. It is suggested that the EMT gene SNAI2/Slug up regulates the stemness gene Sox2, and vice versa, inducing AR expression, promoting metastasis and castration resistance. This approach will provide new sight about the role of the stemness-mesenchymal axis in the metastasis and resistance mechanisms in PCa and their potential control, contributing to develop new therapeutic strategies for patients with metastatic and castration-resistant PCa.

Patients with Positive Lymph Nodes after Radical Prostatectomy and Pelvic Lymphadenectomy-Do We Know the Proper Way of Management?

Lymph node invasion in prostate cancer is a significant prognostic factor indicating worse prognosis. While it significantly affects both survival rates and recurrence, proper management remains a controversial and unsolved issue. The thorough evaluation of risk factors associated with nodal involvement, such as lymph node density or extracapsular extension, is crucial to establish the potential expansion of the disease and to substratify patients clinically. There are multiple strategies that may be employed for patients with positive lymph nodes. Nowadays, therapeutic methods are generally based on observation, radiotherapy, and androgen deprivation therapy. However, the current guidelines are incoherent in terms of the most effective management approach. Future management strategies are expected to make use of novel diagnostic tools and therapies, such as photodynamic therapy or diagnostic imaging with prostate-specific membrane antigen. Nevertheless, this heterogeneous group of men remains a great therapeutic concern, and both the clarification of the guidelines and the optimal substratification of patients are required.

Communicator-Driven Data Preprocessing Improves Deep Transfer Learning of Histopathological Prediction of Pancreatic Ductal Adenocarcinoma

Simple Summary

Pancreatic cancer has a dismal prognosis and its diagnosis can be challenging. Histopathological slides can be digitalized and their analysis can then be supported by computer algorithms. For this purpose, computer algorithms (neural networks) need to be trained to detect the desired tissue type (e.g., pancreatic cancer). However, raw training data often contain many different tissue types. Here we show a preprocessing step using two communicators that sort unfitting tissue tiles into a new dataset class. Using the improved dataset neural networks distinguished pancreatic cancer from other tissue types on digitalized histopathological slides including lymph node metastases.

Abstract

Pancreatic cancer is a fatal malignancy with poor prognosis and limited treatment options. Early detection in primary and secondary locations is critical, but fraught with challenges. While digital pathology can assist with the classification of histopathological images, the training of such networks always relies on a ground truth, which is frequently compromised as tissue sections contain several types of tissue entities. Here we show that pancreatic cancer can be detected on hematoxylin and eosin (H&E) sections by convolutional neural networks using deep transfer learning. To improve the ground truth, we describe a preprocessing data clean-up process using two communicators that were generated through existing and new datasets. Specifically, the communicators moved image tiles containing adipose tissue and background to a new data class. Hence, the original dataset exhibited improved labeling and, consequently, a higher ground truth accuracy. Deep transfer learning of a ResNet18 network resulted in a five-class accuracy of about 94% on test data images. The network was validated with independent tissue sections composed of healthy pancreatic tissue, pancreatic ductal adenocarcinoma, and pancreatic cancer lymph node metastases. The screening of different models and hyperparameter fine tuning were performed to optimize the performance with the independent tissue sections. Taken together, we introduce a step of data preprocessing via communicators as a means of improving the ground truth during deep transfer learning and hyperparameter tuning to identify pancreatic ductal adenocarcinoma primary tumors and metastases in histological tissue sections.

Prognostic Significance of the Extranodal Extension of Regional Lymph Nodes in Stage III-N2 Non-Small-Cell Lung Cancer after Curative Resection

The present study investigated the prognostic role of extranodal extension (ENE) in stage III-N2 non-small-cell lung cancer (NSCLC) following curative surgery. From January 2005 to December 2018, pathologic stage III-N2 disease was diagnosed in 371 patients, all of whom underwent anatomic pulmonary resection accompanied by mediastinal lymph node dissection. This study included 282 patients, after excluding 89 patients who received preoperative chemotherapy or incomplete surgical resection. Their lymph nodes were processed; after hematoxylin and eosin staining, histopathologic slides of the metastatic nodes were reviewed by a designated pathologist. Predictors of disease free survival (DFS), including age, sex, operation type, pathologic T stage, nodal status, visceral pleural invasion, perioperative treatment, and the presence of ENE, were investigated. Among the 282 patients, ENE was detected in 85 patients (30.1%). ENE presence was associated with advanced T stage (p = 0.034), N2 subgroups (p < 0.001), lymphatic invasion (p = 0.001), and pneumonectomy (p = 0.002). The multivariable analysis demonstrated that old age (p < 0.001), advanced T stage (p = 0.012), N2 subgroups (p = 0.005), and ENE presence (p = 0.005) were significant independent predictors of DFS. The DFS rate at five years was 21.4% in patients who had ENE and 43.4% in patients who did not have ENE (p < 0.001). The presence of ENE, coupled with tumor-node-metastasis staging, should be recognized as a meaningful prognostic factor in stage III-N2 NSCLC patients.

Colorectal cancer with microsatellite instability: Right-sided location and signet ring cell histology are associated with nodal metastases, and extranodal extension influences disease-free survival

Colorectal cancer (CRC) with microsatellite instability (MSI) accounts for 15-18 % of all CRCs and represents the category with the best prognosis. This study aimed at determining any possible clinical/pathological features associated with a higher risk of nodal metastasization in MSI-CRC, and at defining any possible prognostic moderators in this setting. All surgically resected CRCs of the last 20 years (mono-institutional series) with a PCR-based diagnosis of MSI, with and without nodal metastasis, have been retrieved for histological review, which was performed following WHO guidelines. Furthermore, the most important prognostic moderators have been investigated with a survival analysis. The study of 33 cases of MSI-CRCs with nodal metastasis highlighted a high fidelity of histology maintenance between primary tumors and matched nodal metastases. At survival analysis, the strongest prognostic variable in MSI-CRCs with nodal metastasis was the extranodal extension (multivariate analysis, HR: 14.4, 95 %CI: 1.46-140.9, p = 0.022). Furthermore, through a comparison between nodal positive (33 cases) and nodal negative (71 cases) MSI-CRCs, right-sided location (p < 0.0001), pT4 stage (p = 0.0004) and signet-ring histology (p = 0.0089) emerged as parameters more commonly associated with nodal metastasization. These findings shed new light on the biology of MSI-CRC and can be of help for the prognostic stratification of MSI-CRC patients.

Prognostic significance of histomorphologic features of lymph node metastases in prostate cancer patients treated with radical prostatectomy: A single center study

OBJECTIVE

We assessed the prognostic value of histomorphologic features of lymph node (LN) metastases in patients with prostate cancer treated with radical prostatectomy MATERIALS AND METHODS: We evaluated the effect of the features of LN metastasis on the risk of biochemical recurrence (BCR) in 280 LN-positive patients who underwent radical prostatectomy between 2006 to 2018. LN specific parameters recorded included number of metastatic LNs, size of the largest metastatic focus, Gleason Grade (GG) of the metastatic focus, and extranodal extension (ENE).

RESULTS

A solitary positive LN was found in 166/280 (59%), 95/280 (34%) patients had 2-4 positive LNs, and 19/280 (7%) had 5 or more positive LNs. The size of the largest metastatic focus > 2 mm (macrometastasis) in 154/261 (59%). GG of the metastatic focus was as follows: GG 1-2: 29/224 (13%); GG 3: 27/224 (12%); and GG 4-5: 168/224 (75%). ENE was identified in 99/244 (41%). We found the number of LNs positive (2-4 vs. 1 Hazard ratio (HR) = 1.60; 95% CI: 1.02 to 2.5; P = 0.04) and GG of the metastatic focus (GG 4&5 vs. 1-3 HR = 1.90; 95% CI: 1.14-3.2; P= 0.014) to be independent predictors of the risk of BCR after surgery on multivariate analysis.

CONCLUSIONS

Our study showed the number of LNs positive and GG of the LN metastatic focus to be significant independent predictors of BCR after radical prostatectomy. We recommend reporting histomorphologic parameters of LN metastasis as they may help in defining BCR risk categorization.

Size and extranodal extension of metastatic lymph nodes in lung adenocarcinoma

Background

This study assessed the prognostic significance of metastatic lymph node size (MLNS) and extranodal extension (EN) in patients with node-positive lung adenocarcinoma (ADC).

Methods

Prognostic factors influencing survival were analyzed, including age, sex, extent of operation, T- and N-stage, size of tumor, postoperative chemotherapy, presence of EN, and MLNS (>7.0 vs. ≤7.0 mm).

Results

Three hundred seventy-five patients met the inclusion criteria were enrolled (mean age: 59.8±10.5 years). Increasing MLNS was significantly correlated with large tumor size (P=0.015), advanced N status (P<0.001), and presence of EN (P<0.001). In multivariable analysis, large tumor size [hazard ratio (HR) 1.135, 95% confidence interval (CI): 1.050 to 1.228, P<0.001], adjuvant chemotherapy (HR 0.582, 95% CI: 0.430 to 0.787, P<0.001), EN (HR 1.454, 95% CI: 1.029 to 2.055, P=0.034), and MLNS greater than 7 mm (HR 1.741, 95% CI: 1.238 to 2.447, P<0.001) were significant prognostic factors for survival. Patients were classified into 3 groups: Group A, MLNS ≤7.0 mm/EN (−); Group B, MLNS ≤7.0 mm/EN (+) or MLNS >7.0 mm/EN (−); and Group C, MLNS >7.0 mm/EN (+). The 5-year overall survival (OS) was 72.2%, 59.0%, and 38.5% in Groups A, B and C, respectively (P<0.001).

Conclusions

The MLNS and presence of EN could provide an important prognostic implication for patients with node-positive lung ADC.

Can 68Ga-prostate specific membrane antigen positron emission tomography/computerized tomography provide an accurate lymph node staging for patients with medium/high risk prostate cancer? A diagnostic meta-analysis

Objective

This article aims to evaluate the diagnostic value of ⁶⁸Gallium-PSMA positron emission tomography/computerized tomography (⁶⁸Ga-PSMA PET/CT) for lymph node (LN) staging in patients with prostate cancer (PCa) by a meta-analysis of diagnostic tests.

Methods

We systematically retrieved articles from Web of Science, EMBASE, Cochrane Database, PubMed. The time limit is from the creation of the database until June 2019, and Stata 15 was used for calculation and statistical analyses.

Results

Sensitivity, specificity, positive and negative likelihood ratio (PLR, NLR), diagnostic odds ratio (DOR) and 95% confidence intervals (CI) be used to evaluate the diagnostic value. A total of 10 studies were included in our meta-analysis, which included 701 individuals. The results of each consolidated summary are as follows: sensitivity of 0.84 (95% CI 0.55–0.95), specificity of 0.95 (95% CI 0.87–0.98), PLR and NLR was 17.19 (95% CI 6.27, 47.17) and 0.17 (95% CI 0.05–0.56), respectively. DOR of 100 (95% CI 18–545), AUC of 0.97 (95% CI 0.95–0.98).

Conclusion

Our study demonstrates that ⁶⁸Ga-PSMA PET/CT has a high overall diagnostic value for LN staging in patients with moderate and high-risk PCa. But our conclusions still require a larger sample size, multi-center prospective randomized controlled trial to verify.

Association Between Contrast-Enhanced Ultrasound Indicators and Prostate Cancer Biochemical Recurrence After Treatment

Background

Some patients with prostate cancer (PCa) will experience biochemical recurrence (BCR) after treatment. Current researches have identified the influencing factors of BCR, but these factors are difficult to quantify and hence unable to accurately predict the BCR in PCa patients.

Objective

To explore the value of contrast-enhanced ultrasound (CEUS) indicators in predicting the BCR after treatment by evaluating the association between them.

Patients and Methods

In a retrospective cohort study, 157 PCa patients were recruited and received prostate specific antigen (PSA) measurement, CEUS, pathological classification, and immunohistochemistry after puncture biopsy. PCa patients with BCR were included in the recurrence group, while the remaining patients were included in the non-recurrence group after a 5-year follow-up. The clinical characteristics and CEUS indicators were compared between the two groups, and the multivariable COX regression was used for screening the influencing factors of BCR. Receiver operating characteristic (ROC) curves were used to analyze the value of potential factors in predicting BCR. The effect of the combined prediction model was explored to improve the accuracy of the prediction.

Results

Twelve patients are lost during the follow-up period and the final analysis included 145 patients. The 5-year BCR rate of PCa patients was 27%, with 43 patients in the recurrence group and 102 patients in the non-recurrence group. Multivariate analysis showed that lymph node metastasis (P<0.001), distant metastasis (P<0.001), Gleason score (P<0.001), pretreatment PSA (P<0.001), treatment method (P<0.001), peak intensity (PI) (P=0.001), and time to peak (TTP) (P=0.003) were independent influencing factors for BCR after treatment. ROC analysis showed that the AUCs of all indicators in predicting BCR were not high (all <0.9). The combination of lymph node metastasis, Gleason score, pretreatment PSA, and treatment method can improve the predictive accuracy (AUC = 0.85), but the AUC was still under 0.9. The combined prediction model including CEUS time-intensity curve (TIC) indicators (PI and TTP) could accurately predict the BCR after treatment (AUC=0.953). The sensitivity and specificity were 93.02% and 88.24%, respectively.

Conclusion

The prediction model including TIC indicators and common influencing factors can more accurately predict the BCR in PCa patients.

Prostate Cancer Nodal Staging: Using Deep Learning to Predict 68Ga-PSMA-Positivity from CT Imaging Alone

Lymphatic spread determines treatment decisions in prostate cancer (PCa) patients. 68Ga-PSMA-PET/CT can be performed, although cost remains high and availability is limited. Therefore, computed tomography (CT) continues to be the most used modality for PCa staging. We assessed if convolutional neural networks (CNNs) can be trained to determine 68Ga-PSMA-PET/CT-lymph node status from CT alone. In 549 patients with 68Ga-PSMA PET/CT imaging, 2616 lymph nodes were segmented. Using PET as a reference standard, three CNNs were trained. Training sets balanced for infiltration status, lymph node location and additionally, masked images, were used for training. CNNs were evaluated using a separate test set and performance was compared to radiologists' assessments and random forest classifiers. Heatmaps maps were used to identify the performance determining image regions. The CNNs performed with an Area-Under-the-Curve of 0.95 (status balanced) and 0.86 (location balanced, masked), compared to an AUC of 0.81 of experienced radiologists. Interestingly, CNNs used anatomical surroundings to increase their performance, "learning" the infiltration probabilities of anatomical locations. In conclusion, CNNs have the potential to build a well performing CT-based biomarker for lymph node metastases in PCa, with different types of class balancing strongly affecting CNN performance.

Efficacy and Safety of Non-Steroidal Anti-Androgens in Patients with Metastatic Prostate Cancer: Meta-Analysis of Randomized Controlled Trials

BACKGROUND

Prostate cancer (PCa) is the sixth primary cause of cancer death. However, conflicts are present about the efficacy and safety of Non-steroidal anti-androgens (NSAA) for its treatment. The aim of this study was to assess the efficacy and safety of NSAAs versus any comparator for the treatment of advanced or metastatic PCa (mPCa).

METHODS

MEDLINE and the Cochrane Library were searched. References of included studies and clinicaltrials.gov were also searched for relevant studies. Only English language studies after 1990 were considered for review. Randomized controlled trials (RCTs) examining the efficacy and safety of NSAAs as compared with any other comparator including surgery or chemotherapy in mPCa patients were included. The outcomes include efficacy, safety and the tolerability of the treatment. The Cochrane Risk of Bias Assessment Tool was used for quality assessment. Two authors were independently involved in the selection, extraction and quality assessment of included studies and disagreements were resolved by discussion or by consulting a third reviewer.

RESULTS

Fifty-eight out of 1307 non-duplicate RCTs with 29154 patients were considered for the review. NSAA showed significantly better progression-free survival [PFS] (Hazard ratio [HR], 0.60; 95% confidence interval [CI], 0.46-0.78; P=0.0001), time to distant metastasis or death [TTD] (HR, 0.80; 95% CI 0.73-0.91; P<0.0001), objective response (Odds ratio [OR], 1.64; 95% CI 1.06-2.54; P=0.03) and clinical benefits (OR, 1.33; 95% CI 1.08-1.63; P=0.006) as compared to the control group. There was no significant difference observed between the groups in terms of overall survival (HR, 0.95; 95%CI, 0.87-1.03; P=0.18) and time to progression (HR, 0.93; 95% CI 0.77-1.11; P=0.43). Treatment-related adverse events were more with the NSAA group, but the discontinuation due to lack of efficacy reason was 43% significantly lesser than the control group in patients with mPCa. Rest of the outcomes were appeared to be non-significant.

CONCLUSION

Treatment with NSAA was appeared to be better efficacious with respect to PFS, TTD, and response rate with considerable adverse events when compared to the control group in patients with metastatic PCa.

Accuracy of standard clinical 3T prostate MRI for pelvic lymph node staging: Comparison to 68Ga-PSMA PET-CT

The aim was to assess the performance of prostate 3T MRI for pelvic lymph node (LN) staging in prostate cancer (PCa), in comparison to ⁶⁸Gallium-prostate specific membrane antigen PET-CT (⁶⁸Ga-PSMA PET-CT) as reference standard for LN detection. 130 patients with PCa underwent non-contrast-enhanced multiparametric prostate 3T MRI and ⁶⁸Ga-PSMA-PET-CT within 180 days at our institution. Overall, 187 LN metastases (n = 43 patients) detected by ⁶⁸Ga-PSMA-PET-CT were characterized by calculating maximum standardized uptake value (SUVmax), area, diameter and anatomical location including iliac, obturator, presacral and inguinal region. MRI achieved an overall sensitivity, specificity, positive and negative predictive value of 81.6% (CI 71.1-88.9%), 98.6% (CI 97.6-99.2%), 73.5% (CI 52.1-87.6%) and 99.5% (CI 98.8-99.8%), respectively. On a region-based analysis, detection rates differed non-significantly (ps > 0.12) in the anatomical regions. On a size-dependent analysis, detection of LN > 10 mm did not differ significantly (ps > 0.09) from LN ≤ 10 mm. In comparison to single T1 sequence evaluation, additional use of the T2 weighted sequences did not improve the overall performance significantly (p > 0.05). 3T prostate MRI represented an accurate tool for the detection of LN compared to ⁶⁸Ga-PSMA-PET-CT. Especially for LN metastases smaller than 10 mm, MRI was less accurate compared to ⁶⁸Ga-PSMA-PET-CT.

Cutaneous Metastasis after Surgery, Injury, Lymphadenopathy, and Peritonitis: Possible Mechanisms

Cutaneous metastases from internal malignancies are uncommon. Umbilical metastasis, also known as Sister Joseph nodule (SJN), develops in patients with carcinomatous peritonitis or superficial lymphadenopathy, while non-SJN skin metastases develop after surgery, injury, and lymphadenopathy. In this review, the possible mechanisms of skin metastases are discussed. SJNs develop by the contiguous or lymphatic spread of tumor cells. After surgery and injury, tumor cells spread by direct implantation or hematogenous metastasis, and after lymphadenopathy, they spread by extranodal extension. The inflammatory response occurring during wound healing is exploited by tumor cells and facilitates tumor growth. Macrophages are crucial drivers of tumor-promoting inflammation, which is a source of survival, growth and angiogenic factors. Angiogenesis is promoted by the vascular endothelial growth factor (VEGF), which also mediates tumor-associated immunodeficiency. In the subcutaneous tissues that surround metastatic lymph nodes, adipocytes promote tumor growth. In the elderly, age-associated immunosuppression may facilitate hematogenous metastasis. Anti-VEGF therapy affects recurrence patterns but at the same time, may increase the risk of skin metastases. Immune suppression associated with inflammation may play a key role in skin metastasis development. Thus, immune therapies, including immune checkpoint inhibitors reactivating cytotoxic T-cell function and inhibiting tumor-associated macrophage function, appear promising.

Ampulla of Vater carcinoma: Molecular landscape and clinical implications

Ampulla of Vater is a peculiar anatomical structure, characterized by the crossroad of three distinct epithelia: Intestinal, ductal pancreatic and biliary. Adenocarcinomas arising in this area represent an opportunity to understand the comparative biology of all periampullary malignancies. These neoplasms can exhibit intestinal, pancreaticobiliary or mixed features, whereas the subclassification based on morphology and immunohistochemical features failed in demonstrating a robust prognostic reliability. In the last few years, the molecular landscape of this tumor entity has been uncovered, identifying alterations that may serve as prognostic and predictive biomarkers. In this review, the histological and genetic characteristics of ampullary carcinomas are discussed, taking into account the main clinical and therapeutic implications related to this tumor type as well.

Assessment of intratumor immune-microenvironment in colorectal cancers with extranodal extension of nodal metastases

BACKGROUND

No data is available on the molecular background of the extra-nodal extension (ENE) of lymph node metastasis (LN) in colorectal cancer (CRC).

METHODS

A series of 22 ENE-positive CRCs was considered and three samples per case were selected (the primary CRC, an ENE-negative and an ENE-positive metastatic LN). Samples (n = 66) were analysed by immunohistochemistry for PD-L1, CD4, CD8, CD68 and CD80. Fifteen out of twenty-two cases were further profiled through a hotspot multigene mutational custom panel, including 164 hotspot regions of AKT1, APC, BRAF, CTNNB1, KIT, KRAS, NRAS, PDGFRA, PIK3CA, PTEN and TP53 genes.

RESULTS

A significantly higher percentage of CD4-, CD8- and CD68-positive cells was observed at the invasive front of both CRCs and in ENE in contrast with what observed at the core of both CRCs and their matched nodal metastases. ENE was also characterized by a significantly higher number of CD80-positive cells. No significant difference was observed in PD-L1 distribution among the different specimens. Fourteen out of 15 CRCs (93%) showed at least a driver mutation. The most frequently mutated gene was TP53 (n = 8 tumors), followed by APC (n = 6), BRAF (n = 4), KRAS, NRAS and PIK3CA (n = 2). In 11 out of 15 CRCs (73%) the mutational profiling of the primary tumor was consistent with what obtained from the two matched LNs.

CONCLUSIONS

A heterogeneous intratumor immune-microenvironment has been observed in ENE-positive CRCs, which are characterized by an increased leukocytic infiltration at the ENE invasive front.

Surgical margin status and its impact on prostate cancer prognosis after radical prostatectomy: a meta-analysis

Background and purpose

Positive surgical margins (PSMs) correlate with adverse outcomes in numerous solid tumours. However, the prognostic value of PSMs in prostate cancer (PCa) patients who underwent radical prostatectomy remains unclear. Herein, we performed a meta-analysis to evaluate the association between PSMs and the prognostic value for biochemical recurrence-free survival (BRFS), cancer-specific survival (CSS), overall survival (OS), cancer-specific mortality (CSM) and overall mortality (OM) in PCa patients.

Materials and methods

According to the PRISMA statement, online databases PubMed, EMBASE and Web of Science were searched to identify relevant studies published prior to February 2018. The hazard ratios (HRs) and 95% confidence intervals (95% CIs) were calculated to evaluate the relationship between PSMs and PCa.

Results

Ultimately, 32 cohort studies that met the eligibility criteria and involved 141,222 patients (51–65,633 per study) were included in this meta-analysis. The results showed that PSMs were significantly predictive of poorer BRFS (HR = 1.35, 95% CI 1.28–1.48, p < 0.001), CSS (HR = 1.49, 95% CI 1.16–1.90, p = 0.001) and OS (HR = 1.11, 95% CI 1.02–1.20, p = 0.014). In addition, PSMs were significantly associated with higher risk of CSM (HR = 1.23, 95% CI 1.16–1.30, p < 0.001) and OM (HR = 1.09, 95% CI 1.02–1.16, p = 0.009) in patients with PCa.

Conclusions

Our study suggests that the presence of a histopathologic PSM is associated with the clinical outcomes BRFS, CSS, OS, CSM and OM in patients with PCa, and PSMs could serve as a poor prognostic factor for patients with PCa.

Electronic supplementary material

The online version of this article (10.1007/s00345-018-2333-4) contains supplementary material, which is available to authorized users.

Extranodal extension of nodal metastases is a poor prognostic moderator in non-small cell lung cancer: a meta-analysis

Extranodal extension (ENE) of nodal metastasis is defined as the extension of metastatic cells through the nodal capsule into the perinodal tissue. This morphological parameter, recently proposed as an important prognostic factor in different types of malignancy, has not been included in the TNM staging system for non-small cell lung cancer (NSCLC). In this systematic review with meta-analysis, we weighted the prognostic role of ENE in patients with lymph node-positive NSCLC. Two independent authors searched SCOPUS and PubMed through 28 February 2017. Prospective and retrospective studies on NSCLC, comparing patients with presence of ENE (ENE+) ENE+) vs. only intranodal extension (ENE-) and including data regarding prognosis, were considered as eligible. Data were summarized using risk ratios (RR) for the number of deaths/recurrences, and hazard ratios (HR) with 95% confidence intervals (CI) for time-dependent risk related to ENE+, adjusted for potential confounders. We identified 13 studies, including 1709 patients (573 ENE+ and 1136 ENE-) with a median follow-up of 60 months. ENE was associated with a significantly increased risk of mortality of all causes (RR = 1.39, 95% CI: 1.18-1.65, P < 0.0001, I² = 70%; HR = 1.30, 95% CI: 1.01-1.67, P = 0.04, I² = 0%) and of disease recurrence (RR = 1.32, 95% CI: 1.04-1.68, P = 0.02, I² = 42%; HR = 1.93, 95% CI: 1.53-2.44, P < 0.0001, I² = 0%). We conclude that in NSCLC, requirements for assessment of ENE should be included in gross sampling and ENE status should be included in the pathology report. Inclusion of ENE status in oncology staging systems will allow further assessment of its role as prognostic parameter.

Prostate cancer reporting and staging: needle biopsy and radical prostatectomy specimens

Prostatic adenocarcinoma remains the most common cancer affecting men. A substantial majority of patients have the diagnosis made on thin needle biopsies, most often in the absence of a palpable abnormality. Treatment choices ranging from surveillance to radical prostatectomy or radiation therapy are largely driven by the pathologic findings in the biopsy specimen. The first part of this review focuses on important morphologic parameters in needle biopsy specimens that are not covered in the accompanying articles. This includes tumor quantification as well as other parameters such a extraprostatic extension, seminal vesicle invasion, perineural invasion, and lymphovascular invasion. For those men who undergo radical prostatectomy, pathologic stage and other parameters are critical in prognostication and in determining the appropriateness of adjuvant therapy. Staging parameters, including extraprostatic extension, seminal vesicle invasion, and lymph node status are discussed here. Surgical margin status is also an important parameter and definitions and reporting of this feature are detailed. Throughout the article the current reporting guidelines published by the College of American Pathologists and the International Collaboration on Cancer Reporting are highlighted.