Immunoscore immune checkpoint using spatial quantitative analysis of CD8 and PD-L1 markers is predictive of the efficacy of anti- PD1/PD-L1 immunotherapy in non-small cell lung cancer

BACKGROUND

Anti-PD-1 and PD-L1 antibodies (mAbs) are approved immunotherapy agents to treat metastatic non-small cell lung cancer (NSCLC) patients. Only a minority of patients responds to these treatments and biomarkers predicting response are currently lacking.

METHODS

Immunoscore-Immune-Checkpoint (Immunoscore-IC), an in vitro diagnostic test, was used on 471 routine single FFPE-slides, and the duplex-immunohistochemistry CD8 and PD-L1 staining was quantified using digital-pathology. Analytical validation was performed on two independent cohorts of 206 NSCLC patients. Quantitative parameters related to cell location, number, proximity and clustering were analysed. The Immunoscore-IC was applied on a first cohort of metastatic NSCLC patients (n = 133), treated with anti-PD1 or anti-PD-L1 mAbs. Another independent cohort (n = 132) served as validation.

FINDINGS

Anti-PDL1 clone (HDX3) has similar characteristics as anti-PD-L1 clones (22C3, SP263). Densities of PD-L1+ cells, CD8+ cells and distances between CD8+ and PD-L1+ cells were quantified and the Immunoscore-IC classification was computed. Using univariate Cox model, 5 histological dichotomised variables (CD8 free of PD-L1+ cells, CD8 clusters, CD8 cells in proximity of PD-L1 cells, CD8 density and PD-L1 cells in proximity of CD8 cells) were significantly associated with Progression-Free Survival (PFS) (all P < 0.0001). Immunoscore-IC classification improved the discriminating power of prognostic model, which included clinical variables and pathologist PD-L1 assessment. In two categories, the Immunoscore-IC risk-score was significantly associated with patients' PFS (HR = 0.39, 95% CI (0.26-0.59), P < 0.0001) and Overall Survival (OS) (HR = 0.42, 95% CI (0.27-0.65), P < 0.0001) in the training-set. Further increased hazard ratios (HR) were found when stratifying patients into three-category Immunoscore-IC (IS-IC). All patients with Low-IS-IC progressed in less than 18 months, whereas PFS at 36 months were 34% and 33% of High-IS-IC patients in the training and validation sets, respectively.

INTERPRETATION

Immunoscore-IC is a powerful tool to predict the efficacy of immune-checkpoint inhibitors (ICIs) in patients with NSCLC.

FUNDING

Veracyte, INSERM, Labex Immuno-Oncology, Transcan ERAnet European project, ARC, SIRIC, CARPEM, Ligue Contre le Cancer, ANR, QNRF, INCa France, Louis Jeantet Prize Foundation.

Efficacy of anti-PD1/PD-L1 immunotherapy in non–small cell lung cancer is dependent upon Immunoscore IC CD8 and PD-L1 status

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Background: Anti-PD1 and PD-L1 antibodies (mAb) are immune checkpoint inhibitors (ICIs) to treat patients with metastatic non–small cell lung cancer (NSCLC). Unfortunately, only a handful of patients respond to ICIs. Methods: A cohort of patients with metastatic NSCLC (n=133) treated with anti-PD1 or anti-PD-L1 mAb in two independent care centers was evaluated. An independent cohort of 132 patients from another hospital was used as a validation. Immunoscore IC, an in vitro diagnostic test (CE-IVD), was used on a routine single FFPE slide, and duplex immunohistochemistry CD8 and PD-L1 staining was quantified using digital pathology. Quantitative and spatial parameters related to cell location, number, proximity, and clustering were analyzed. An Immunoscore IC–based model discriminated patients into 2 categories or 3 categories. Results: Anti–PD-L1 clone (HDX3) had similar characteristics as other anti–PD-L1 clones (22C3, SP263) with a mean overall agreement above 95%. Intra- and inter-laboratory concordances for classifying patients at 1% cut-off according to digital anti–PD-L1 (HDX3) were 100% and 94%, respectively. Routine laboratory evaluation of PD-L1 expression showed an agreement with digital anti–PD-L1 quantification of 92% and 97% at 1% and 50% cut-offs, respectively. Using univariate Cox model after FDR correction, 5 pathological dichotomized variables were significantly associated with PFS (all p < 0.0001). These variables included: CD8 free of PD-L1, CD8 clusters, CD8 cells in proximity of PD-L1 cells, CD8 number, PD-L1 cells in proximity of CD8 cells. Similar results were found using univariate Cox analysis on continuous variables (all p < 0.003) in two independent cohorts of patients. Using multivariate Cox model Immunoscore IC classification improved the discriminating power of prognostic model, which included clinical variables and pathologist PD-L1 assessment. In two categories, the Immunoscore IC risk score was significantly associated with both patients’ PFS (p < 0.0001) and OS (p < 0.0001) in the training cohort and in the validation cohort (PFS: p = 0.0047, OS: p < 0.0001). Further increased hazard ratios were found when stratifying patients into 3 categories of Immunoscore IC. At 6 months, PFS rates were 10% versus 60% in the training cohort and 20% versus 62% in the validation cohort for high-risk and low-risk Immunoscore IC score, respectively. All patients (100%) with high-risk Immunoscore IC score relapsed in less than 18 months, in contrast to 34% and 33% of low-risk Immunoscore IC patients who did not relapse for more than 36 months in the training and validation cohorts, respectively. Conclusions: These data underline that Immunoscore IC is a potent tool to predict the efficacy of ICIs in patients with NSCLC. Immunoscore IC characterized patients who are resistant to ICIs.

Establishment of a pancreatic adenocarcinoma molecular gradient (PAMG) that predicts the clinical outcome of pancreatic cancer

BACKGROUND

A significant gap in pancreatic ductal adenocarcinoma (PDAC) patient's care is the lack of molecular parameters characterizing tumours and allowing a personalized treatment.

METHODS

Patient-derived xenografts (PDX) were obtained from 76 consecutive PDAC and classified according to their histology into five groups. A PDAC molecular gradient (PAMG) was constructed from PDX transcriptomes recapitulating the five histological groups along a continuous gradient. The prognostic and predictive value for PMAG was evaluated in: i/ two independent series (n = 598) of resected tumours; ii/ 60 advanced tumours obtained by diagnostic EUS-guided biopsy needle flushing and iii/ on 28 biopsies from mFOLFIRINOX treated metastatic tumours.

FINDINGS

A unique transcriptomic signature (PAGM) was generated with significant and independent prognostic value. PAMG significantly improves the characterization of PDAC heterogeneity compared to non-overlapping classifications as validated in 4 independent series of tumours (e.g. 308 consecutive resected PDAC, uHR=0.321 95% CI [0.207-0.5] and 60 locally-advanced or metastatic PDAC, uHR=0.308 95% CI [0.113-0.836]). The PAMG signature is also associated with progression under mFOLFIRINOX treatment (Pearson correlation to tumour response: -0.67, p-value < 0.001).

INTERPRETATION

PAMG unify all PDAC pre-existing classifications inducing a shift in the actual paradigm of binary classifications towards a better characterization in a gradient.

FUNDING

Project funding was provided by INCa (Grants number 2018-078 and 2018-079, BACAP BCB INCa_6294), Canceropole PACA, DGOS (labellisation SIRIC), Amidex Foundation, Fondation de France, INSERM and Ligue Contre le Cancer.

Pancreatic Cancer Organoids for Determining Sensitivity to Bromodomain and Extra-Terminal Inhibitors (BETi)

Pancreatic ductal adenocarcinoma (PDAC) is a heterogeneous disease, therefore stratification of patients is essential to predict their responses to therapies and to choose the best treatment. PDAC-derived organoids were produced from PDTX and Endoscopic Ultrasound-Guided Fine-Needle Aspiration (EUS-FNA) biopsies. A signature based on 16 genes targets of the c-MYC oncogene was applied to classify samples into two sub-groups with distinctive phenotypes named MYC-high and MYC-low. The analysis of 9 PDTXs and the corresponding derived organoids revealed that this signature which was previously designed from PDTX is transferable to the organoid model. Primary organoids from 24 PDAC patients were treated with NHWD-870 or JQ1, two inhibitors of c-MYC transcription. Notably, the comparison of their effect between the two sub-groups showed that both compounds are more efficient in MYC-high than in MYC-low samples, being NHWD-870 the more potent treatment. In conclusion, this study shows that the molecular signatures could be applied to organoids obtained directly from PDAC patients to predict the treatment response and could help to take the more appropriate therapeutic decision for each patient in a clinical timeframe.

Efficacy of Immune Checkpoint Inhibitors in KRAS-Mutant Non-Small Cell Lung Cancer (NSCLC)

INTRODUCTION

KRAS mutation is the most frequent molecular alteration found in advanced NSCLC; it is associated with a poor prognosis without available targeted therapy. Treatment options for NSCLC have been recently enriched by the development of immune checkpoint inhibitors (ICIs), and data about its efficacy in patients with KRAS-mutant NSCLC are discordant. This study assessed the routine efficacy of ICIs in advanced KRAS-mutant NSCLC.

METHODS

In this retrospective study, clinical data were extracted from the medical records of patients with advanced NSCLC treated with ICIs and with available molecular analysis between April 2013 and June 2017. Analysis of programmed death ligand 1 (PD-L1) expression was performed if exploitable tumor material was available.

RESULTS

A total of 282 patients with ICI-treated (in the first line or more) advanced NSCLC (all histological subgroups) who were treated with ICIs (anti-programmed death 1, anti-PD-L1, or anti-cytotoxic T-lymphocyte associated protein 4 antibodies), including 162 (57.4%) with KRAS mutation, 27 (9.6%) with other mutations, and 93 (33%) with a wild-type phenotype, were identified. PD-L1 analysis was available for 128 patients (45.4%), of whom 45.3% and 19.5% had PD-L1 expression of 1% or more and 50%, respectively (49.5% and 21.2%, respectively, in the case of the 85 patients with KRAS-mutant NSCLC). No significant difference was seen in terms of objective response rates, progression-free survival, or overall survival between KRAS-mutant NSCLC and other NSCLC. No significant differences in overall survival or progression-free survival were observed between the major KRAS mutation subtypes (G12A, G12C, G12D, G12V, and G13C). In KRAS-mutant NSCLC, unlike in non-KRAS-mutant NSCLC, the efficacy of ICIs is consistently higher, even though not statistically significant, for patients with PD-L1 expression in 1% or more of tumor cells than for those with PD-L1 expression in less than 1% of tumor cells, and this finding is especially true when PD-L1 expression is high (PD-L1 expression ≥50%).

CONCLUSION

For patients with KRAS-mutant NSCLC (all mutational subtypes), the efficacy of ICI is similar to that for patients with other types of NSCLC. PD-L1 expression seems to be more relevant for predicting the efficacy of ICIs in KRAS-mutant NSCLC than it is in other types of NSCLC.

[An ovarian tumor can hide another one]

We report the case of a 33-year-old woman who went under surgery for a cystic mature teratoma. The histological exam found two cysts, one was a mature teratoma and the other was a struma ovarii with a papillary carcinomatous element. Struma ovarii cancerization is seen in 5 to 10% of the cases usually under a papillary carcinoma type. Diagnosis is rarely made before surgery, the patients exceptionally show thyroid symptoms. Histologically, the tumour presents the same way as the one seen in the thyroid gland and BRAF mutations have been reported. The problem concerns ovarian metastases of a thyroid cancer. A normal thyroid check up and normal thyroid tissue close to the tumor in the ovary are in favor for a cancerize struma ovarii. The therapeutic care is not consensual, going from an annexectomy to hysterectomy and bilateral annexectomy. The patients must be followed on long-term with thyroglobulin quantitative analysis for at least 10 years and whole body scintigraphy with iodine 123 to detect relapse or metastases. The prognosis is usually good but precise criteria are still to define.

Is negative multiparametric magnetic resonance imaging really able to exclude significant prostate cancer? The real-life experience

OBJECTIVES

To evaluate the histopathological results after radical prostatectomy (RP) in patients that had normal preoperative multiparametric magnetic resonance imaging (mpMRI), in order to determine whether they had significant or insignificant disease. Moreover, we evaluated the influence of the expertise of the radiologist on the results.

PATIENTS AND METHODS

We retrospectively included patients who underwent RP in our centre and who had a preoperative negative mpMRI. The MRIs were considered negative when no suspicious lesion was seen or when the Prostate Imaging Reporting and Data System version 1 score was <7. We used Pathological tumour-node-metastasis staging and Gleason score on pathology reports, and whole-mount sections to calculate tumour volume.

RESULTS

We identified 101 patients from 2009 to 2015. Final pathology showed that 16.9% had extraprostatic extension, 13.8% had primary Gleason pattern 4 (4 + 3 and above), 47.5% had secondary Gleason pattern 4 or 5, and 55.9% and 20.6% had a main tumour volume of ≥0.5 and ≥2 mL, respectively. When limiting the analysis to expert reading only, the numbers improved: only one patient (3.4%) had extraprostatic extension (P < 0.05), one patient (3.4%) had primary Gleason pattern 4 (P = 0.05), and 64.7% and 5.9% had a main tumour volume of ≥0.5 and ≥2 mL, respectively (P = 0.01).

CONCLUSION

A negative MRI does not guarantee the absence of significant prostate cancer.