Measured residual tumor cellularity correlates with survival in neoadjuvant treated pancreatic ductal adenocarcinomas

Biomarker dynamics affecting neoadjuvant therapy response and outcome of HER2-positive breast cancer subtype

HER2+ breast cancer (BC) is an aggressive subtype genetically and biologically heterogeneous. We evaluate the predictive and prognostic role of HER2 protein/gene expression levels combined with clinico-pathologic features in 154 HER2+ BCs patients who received trastuzumab-based neoadjuvant chemotherapy (NACT). The tumoral pathological complete response (pCR) rate was 40.9%. High tumoral pCR show a scarce mortality rate vs subjects with a lower response. 93.7% of ypT0 were HER2 IHC3+ BC, 6.3% were HER2 IHC 2+/SISH+ and 86.7% of ypN0 were HER2 IHC3+, the remaining were HER2 IHC2+/SISH+. Better pCR rate correlate with a high percentage of infiltrating immune cells and right-sided tumors, that reduce distant metastasis and improve survival, but no incidence difference. HER2 IHC score and laterality emerge as strong predictors of tumoral pCR after NACT from machine learning analysis. HER2 IHC3+ and G3 are poor prognostic factors for HER2+ BC patients, and could be considered in the application of neoadjuvant therapy. Increasing TILs concentrations, lower lymph node ratio and lower residual tumor cellularity are associated with a better outcome. The immune microenvironment and scarce lymph node involvement have crucial role in clinical outcomes. The combination of all predictors might offer new options for NACT effectiveness prediction and stratification of HER2+ BC during clinical decision-making.

Artificial Intelligence-Based Segmentation of Residual Tumor in Histopathology of Pancreatic Cancer after Neoadjuvant Treatment

Simple Summary

The use of neoadjuvant therapy (NAT) in patients with pancreatic ductal adenocarcinoma (PDAC) is increasing. Objective quantification of the histopathological response to NAT may be used to guide adjuvant treatment and compare the efficacy of neoadjuvant regimens. However, current tumor response scoring (TRS) systems suffer from interobserver variability, originating from subjective definitions, the sometimes challenging histology, and response heterogeneity throughout the tumor bed. This study investigates if artificial intelligence-based segmentation of residual tumor burden in histopathology of PDAC after NAT may offer a more objective and reproducible TRS solution.

Abstract

Background: Histologic examination of resected pancreatic cancer after neoadjuvant therapy (NAT) is used to assess the effect of NAT and may guide the choice for adjuvant treatment. However, evaluating residual tumor burden in pancreatic cancer is challenging given tumor response heterogeneity and challenging histomorphology. Artificial intelligence techniques may offer a more reproducible approach. Methods: From 64 patients, one H&E-stained slide of resected pancreatic cancer after NAT was digitized. Three separate classes were manually outlined in each slide (i.e., tumor, normal ducts, and remaining epithelium). Corresponding segmentation masks and patches were generated and distributed over training, validation, and test sets. Modified U-nets with varying encoders were trained, and F1 scores were obtained to express segmentation accuracy. Results: The highest mean segmentation accuracy was obtained using modified U-nets with a DenseNet161 encoder. Tumor tissue was segmented with a high mean F1 score of 0.86, while the overall multiclass average F1 score was 0.82. Conclusions: This study shows that artificial intelligence-based assessment of residual tumor burden is feasible given the promising obtained F1 scores for tumor segmentation. This model could be developed into a tool for the objective evaluation of the response to NAT and may potentially guide the choice for adjuvant treatment.

Dataset for the reporting of carcinoma of the exocrine pancreas: recommendations from the International Collaboration on Cancer Reporting (ICCR)

BACKGROUND AND OBJECTIVES

Current guidelines for the pathology reporting on pancreatic cancer differ in certain aspects, resulting in divergent reporting practice and a lack of comparability of data. Here we report on a new international dataset for the pathology reporting of resection specimens with cancer of the exocrine pancreas (ductal adenocarcinoma and acinar cell carcinoma). The dataset was produced under the auspices of the International Collaboration on Cancer Reporting (ICCR), a global alliance of major (inter-)national pathology and cancer organisations.

METHODS AND RESULTS

According to the ICCR's rigorous process for dataset development, an international expert panel consisting of pancreatic pathologists, a pancreatic surgeon and an oncologist produced a set of core and non-core data items based on a critical review and discussion of current evidence. Commentary was provided for each data item to explain the rationale for selecting it as a core or non-core element, its clinical relevance, and to highlight potential areas of disagreement or lack of evidence, in which case a consensus position was formulated. Following international public consultation, the document was finalised and ratified, and the dataset, which includes a synoptic reporting guide, was published on the ICCR website.

CONCLUSIONS

This first international dataset for cancer of the exocrine pancreas is intended to promote high quality, standardised pathology reporting. Its widespread adoption will improve consistency of reporting, facilitate multidisciplinary communication and enhance comparability of data, all of which will help to improve the management of pancreatic cancer patients.

Scoring of tumour response after neoadjuvant therapy in resected pancreatic cancer: systematic review

BACKGROUND

Preoperative chemo(radio)therapy is used increasingly in pancreatic cancer. Histological evaluation of the tumour response provides information on the efficacy of preoperative treatment and is used to determine prognosis and guide decisions on adjuvant treatment. This systematic review aimed to provide an overview of the current evidence on tumour response scoring systems in pancreatic cancer.

METHODS

Studies reporting on the assessment of resected pancreatic ductal adenocarcinoma following neoadjuvant chemo(radio)therapy were searched using PubMed and EMBASE. All original studies reporting on histological tumour response in relation to clinical outcome (survival, recurrence-free survival) or interobserver agreement were eligible for inclusion. This systematic review followed the PRISMA guidelines.

RESULTS

The literature search yielded 1453 studies of which 25 met the eligibility criteria, revealing 13 unique scoring systems. The most frequently investigated tumour response scoring systems were the College of American Pathologists system, Evans scoring system, and MD Anderson Cancer Center system, investigated 11, 9 and 5 times respectively. Although six studies reported a survival difference between the different grades of these three systems, the reported outcomes were often inconsistent. In addition, 12 of the 25 studies did not report on crucial aspects of pathological examination, such as the method of dissection, sampling approach, and amount of sampling.

CONCLUSION

Numerous scoring systems for the evaluation of tumour response after preoperative chemo(radio)therapy in pancreatic cancer exist, but comparative studies are lacking. More comparative data are needed on the interobserver variability and prognostic significance of the various scoring systems before best practice can be established.

A Critical Assessment of Postneoadjuvant Therapy Pancreatic Cancer Regression Grading Schemes With a Proposal for a Novel Approach

Currently, there is no consensus on the optimal tumor response score (TRS) system to assess regression in pancreatic cancers resected after neoadjuvant therapy. We developed a novel TRS (Royal North Shore [RNS] system) based on estimating the percentage of tumor bed occupied by viable cancer and categorized into 3 tiers: grade 1 (≤10%), grade 2 (11% to 75%), and grade 3 (>75%). We assessed 147 resected carcinomas with this and other TRS systems (College of American Pathologists [CAP], MD Anderson Cancer Center [MDACC], and Evans). The 3-tiered RNS system predicted median survival after surgery for grades 1, 2, and 3 of 54, 23, and 9 months, respectively (P<0.05). The CAP, MDACC, and Evans systems also predicted survival (P<0.05) but less consistently. The median survival for MDACC and CAP grade 0 (complete regression) was less than MDACC grade 1 and CAP grades 1 and 2. There was no difference in survival between CAP grades 2 and 3 (P=0.960), Evans grades 1 and 2a (P=0.395), and Evans grades 2a and 2b (P=0.587). Interobserver concordance was weak for CAP (κ=0.431), moderate for MDACC (κ=0.691), minimal for Evans (κ=0.307), and moderate to strong for RNS (κ=0.632 to 0.84). Of age, sex, size, stage, grade, perineural and vascular invasion, extrapancreatic extension, margin status, and RNS score, only RNS score, vascular invasion, and extrapancreatic extension predicted survival in univariate analysis. Only extrapancreatic extension (P=0.034) and RNS score (P<0.0001) remained significant in multivariate analysis. We conclude that the RNS system is a reproducible and powerful predictor of survival after resection for pancreatic cancers treated with neoadjuvant therapy and should be investigated in larger cohorts.

Amsterdam International Consensus Meeting: tumor response scoring in the pathology assessment of resected pancreatic cancer after neoadjuvant therapy

Histopathologically scoring the response of pancreatic ductal adenocarcinoma (PDAC) to neoadjuvant treatment can guide the selection of adjuvant therapy and improve prognostic stratification. However, several tumor response scoring (TRS) systems exist, and consensus is lacking as to which system represents best practice. An international consensus meeting on TRS took place in November 2019 in Amsterdam, The Netherlands. Here, we provide an overview of the outcomes and consensus statements that originated from this meeting. Consensus (≥80% agreement) was reached on a total of seven statements: (1) TRS is important because it provides information about the effect of neoadjuvant treatment that is not provided by other histopathology-based descriptors. (2) TRS for resected PDAC following neoadjuvant therapy should assess residual (viable) tumor burden instead of tumor regression. (3) The CAP scoring system is considered the most adequate scoring system to date because it is based on the presence and amount of residual cancer cells instead of tumor regression. (4) The defining criteria of the categories in the CAP scoring system should be improved by replacing subjective terms including "minimal" or "extensive" with objective criteria to evaluate the extent of viable tumor. (5) The improved, consensus-based system should be validated retrospectively and prospectively. (6) Prospective studies should determine the extent of tissue sampling that is required to ensure adequate assessment of the residual cancer burden, taking into account the heterogeneity of tumor response. (7) In future scientific publications, the extent of tissue sampling should be described in detail in the "Materials and methods" section.