METHODS FOR PREDICTING THE RISK OF RECURRENCE AND/OR DEATH OF PATIENTS SUFFERING FROM A SOLID CANCER AFTER PREOPERATIVE ADJUVANT THERAPIES

Abstract

The inventors assessed in locally advanced rectal cancer whether a diagnostic biopsy-adapted Immunoscore (ISg) could predict response to neoadjuvant treatment (nT) and better define patients eligible to an organ preservation strategy (“Watch-and-Wait”). The inventors showed that IS.sub.B was an independent parameter, more informative than pre- (P<0.001) and post-nT (P<0.05) imaging to predict disease-free survival. IS.sub.B combined with imaging post-nT discriminated very good responders that could benefit from organ preservation strategy. Accordingly, the present invention relates to methods for predicting the recurrence and/or death of patients suffering from a solid cancer after preoperative adjuvant therapies.

Claims

1. A method of predicting the risk of recurrence and/or death of a patient suffering from a solid cancer after preoperative adjuvant therapy and treating the patient comprising determining i) an arithmetic mean value of percentile of an immune response of the patient before the preoperative adjuvant therapy, and ii) a clinical response determined after the preoperative adjuvant therapy; treating, by radical surgery and/or adjuvant therapy, the subject determined to have iii) an arithmetic mean value of percentile of an immune response that is lower than a predetermined reference arithmetic mean value of percentile, and iv) a partial clinical response or no clinical response to the preoperative adjuvant therapy.

2. The method of claim 1 wherein the patient suffers from a primary cancer or from a metastatic cancer.

3. The method of claim 1 wherein the patient suffers from a locally advanced cancer.

4. The method of claim 1 wherein the patient suffers from a locally advanced rectal cancer.

5. The method of claim 1 wherein the preoperative adjuvant therapy comprises radiotherapy, chemotherapy, a targeted therapy, a hormone therapy, an immunotherapy or a combination thereof.

6. The method of claim 1 wherein the preoperative adjuvant therapy comprises a combination of radiotherapy and chemotherapy.

7. The method of claim 1 wherein the immune response is assessed by quantifying one or more immune markers determined in a biopsy tumor sample obtained from the patient before the preoperative adjuvant chemotherapy.

8. The method of claim 7 wherein the one or more immune markers comprise the density of CD3+ cells, the density of CD8+ cells, the density of CD45RO+ cells, the density of GZM-B+ cells, the density of CD103+ cells and/or the density of B cells.

9. The method of claim 7 wherein the one or more immune markers comprise the density of CD3+ cells and the density of CD8+ cells, the density of CD3+ cells and the density of CD45RO+ cells, the density of CD3+ cells the density of GZM-B+ cells, the density of CD8+ cells and the density of CD45RO+ cells, the density of CD8+ cells and the density of GZM-B+ cells; the density of CD45RO+ cells and the density of GZM-B+ cells or the density of CD3+ cells and the density of CD103+ cells.

10. The method of claim 9 wherein the density of CD3+ cells and the density of CD8+ cells is determined in the tumor biopsy sample.

11. The method of claim 7 wherein the one or more immune markers comprise the expression level of one or more genes from the group consisting of CCR2, CD3D, CD3E, CD3G, CD8A, CXCL10, CXCL11, GZMA, GZMB, GZMK, GZMM, IL15, IRF1, PRF1, STAT1, CD69, ICOS, CXCR3, STAT4, CCL2, and TBX21.

12. The method of claim 7 wherein the one or more immune markers comprise the expression level of one or more genes from the group consisting of GZMH, IFNG, CXCL13, GNLY, LAG3, ITGAE, CCL5, CXCL9, PF4, IL17A, TSLP, REN, IHH, PROM1 and VEGFA.

13. The method according of claim 7 wherein the one or more immune markers comprise an expression level of at least one gene representative of human adaptive immune response and an expression level of at least one gene representative of human immunosuppressive response.

14. The method of claim 13 wherein the at least one gene representative of human adaptive immune response is selected from the group consisting of CCL5, CCR2, CD247, CD3E, CD3G, CD8A, CX3CL1, CXCL11, GZMA, GZMB, GZMH, GZMK, IFNG, IL15, IRF1, ITGAE, PRF1, STAT1 and TBX21 and said at least one gene representative of human immunosuppressive response is selected from the group consisting of CD274, CTLA4, IHH, IL17A, PDCD1, PF4, PROM1, REN, TIM-3, TSLP, and VEGFA.

15. The method of claim 7 wherein the immune response is assessed by a scoring system that involves the steps of: a) quantifying the one or more immune markers in a tumor biopsy sample obtained from said patient; b) comparing each values-obtained at step a) for said one or more immune markers with a distribution of values obtained for each of said one or more immune markers from a reference group of patients suffering from said cancer; c) determining for each values obtained at step a) for said one or more immune markers the percentile of the distribution to which the values obtained at step a) correspond; d) calculating the arithmetic mean value or the median value of percentile.

16. The method of claim 15 wherein the immune response is assessed by a continuous-scoring system comprising the steps of: a) quantifying the density of CD3+ cells and the density of CD8+ cells in a tumor biopsy sample obtained from said patient; b) comparing each density values obtained at step a) with a distribution of values obtained from a reference group of patients suffering from said cancer; c) determining for each density values obtained at step a) the percentile of the distribution to which the values obtained at step a) correspond; d) calculating the arithmetic mean value of percentile.

17. The method of claim 15 wherein the immune response is assessed by a non-continuous scoring system that involves the steps of: a) quantifying the density of CD3+ cells and the density of CD8+ cells in a tumor biopsy sample obtained from said patient; b) comparing each density values obtained at step a) with a distribution of values obtained from a reference group of patients suffering from said cancer; c) determining for each density values obtained at step a) the percentile of the distribution to which the values obtained at step a) correspond; d) calculating the arithmetic mean value of percentile; and e) comparing the arithmetic mean value obtained at step d) with a predetermined reference arithmetic mean value of percentile, and f) assigning a low or high score depending on whether the arithmetic mean value of percentile is respectively lower or higher than the predetermined reference arithmetic mean value of percentile.

18. The method of claim 15 wherein the immune response is assessed by a non-continuous scoring system that involves the steps of: a) quantifying the density of CD3+ cells and the density of CD8+ cells in a tumor biopsy sample obtained from said patient; b) comparing each density values obtained at step a) with a distribution of values obtained from a reference group of patients suffering from said cancer; c) determining for each density values obtained at step a) the percentile of the distribution to which the values obtained at step a) correspond; d) calculating the arithmetic mean value of percentile; and e) comparing the arithmetic mean value of percentile obtained at step d) with 2 predetermined reference arithmetic mean values percentile, and f) assigning a low, intermediate or high score when the arithmetic mean value: is lower than the lowest predetermined reference arithmetic mean value of percentile is comprised between the 2 predetermined reference arithmetic mean values of percentile or is higher than the highest predetermined reference arithmetic mean value of percentile, respectively.

19. The method of claim 1 wherein the clinical response is determined by the assessment of the level of ctDNA.

20. The method of claim 1 wherein the clinical response is determined by the assessment of reduction in tumor volume that is assessed by imaging.

21. The method of claim 20 wherein the clinical response is assessed by radiography, ultrasound imaging, magnetic resonance, scintigraphy, or Tomography Emission Positron/Computed Tomography (PET/CT).

22. The method of claim 1 wherein the clinical response is assessed by the ycTNM scoring system.

23. The method of claim 1 that comprises the steps of: a) assessing at least two parameters, wherein the first parameter is the immune response determined before the preoperative adjuvant therapy and the second parameter is the clinical response determined after the preoperative adjuvant therapy b) implementing an algorithm on data comprising the parameters assessed at step a) as to obtain an algorithm output, the implementing step being computer-implemented; and c) determining the risk of recurrence and/or death from the algorithm output obtained at step b).

24. The method of claim 1, wherein when the clinical response is ycTNM=0-I, the higher the arithmetic mean or median value of percentile, the lower is the risk of recurrence and/or death, the longer is the survival time of the patient, and an organ preservation strategy is implemented.

25. The method of claim 1, wherein when the clinical response is ycTNM=0-I, and the arithmetic mean or median value of percentile is classified as “high”, the patient has a low risk of recurrence and/or death, the survival time of the patient is long, and an organ preservation strategy is implemented.

Description

FIGURES

[0247] FIG. 1. Disease-free survival according to IS.sub.B Low, IS.sub.B Intermediate (Int.), and IS.sub.B High in patients with A) ycTNM=0 or I and B) ycTNM=II, III or IV, as determined by imaging post-neoajuvant therapy. P test for trend (P (tft)) is determined by log rank test for trend.

[0248] FIG. 2. Probability of the 2-year and 5-year Disease-free survival according to IS.sub.B expressed as a continuous variable (IS.sub.B mean score, in percentiles) in patients with A) ycTNM=0 or I and B) ycTNM=II, III or IV, as determined by imaging post-neoajuvant therapy, under the Cox proportional hazards regression model.

[0249] FIG. 3. Forest plots for Disease-free survival illustrating the hazard ratio according to IS.sub.B Low vs Intermediate (Int.) and Low vs High, in patients with ycTNM=0 or I and ycTNM=II, III or IV, as determined by imaging post-neoajuvant therapy.

EXAMPLE

[0250] Patients and Methods:

[0251] Patient Population

[0252] Two retrospective consecutive cohorts of LARC patients (n.sub.1=131, n.sub.2=118) with available biopsies, treated by nT and radical surgery by total mesorectal excision (TME) were analyzed. Cohort 1 was a monocentric cohort and cohort 2 was multicentric (Table 1). Inclusion period ranged from 1999 to 2016. Neoadjuvant treatment and surgery criteria were defined by each institution. Overall, 64.2% of patients were male and the median age at diagnosis was 65 (interquartile range [IQR]=53.3-74.1). Patients were treated by nT (short [3.7%] or long [96.3%] course of radiation; 5-fluorouracil-based chemotherapy [CT; 82%]; 18% did not receive CT). Rectal tumors were classified as cTNM (UICC TNM 8.sup.th edition) I (1.2%), II (27.3%), III (71.5%) according to baseline staging information provided by pelvic magnetic resonance and chest/abdominal computed tomography imaging. An additional cohort of patients (n=73) with a complete/nearly complete response to nT (ycTNM 0-1), followed by a Watch-and-Wait strategy, was analyzed (Table 2). The median duration of follow-up for DFS of the cohort 1+2 was 45.4 months (IQR=25.7-65.6). Duration of follow-up of each cohort for DFS, TTR and OS with the number of events is provided in Table 3. The study was approved by an ethical review board of each center.

[0253] Clinical Outcomes

[0254] Patients were compared according to the degree of tumoral response to nT, using different tumor regression grade (TRG) scoring systems: i/ the Dworak classification (21) defined as complete (Dworak 4), near complete (Dworak 3), moderate (Dworak 2), minimal (Dworak 1) and no regression (Dworak 0), ii/ the neoadjuvant rectal (NAR) score classification (5), calculated using the equation [5pN-3(cT-pT)+12]{circumflex over ( )}2/9.61, and classified as low (<8), intermediate (8-16), and high (>16), iii/ the ypTNM stage, ie. the postsurgical pathological T and N evaluation, and iv/ downstaging of the tumor (4), defined as complete (ypT0N0), intermediate (ypT1-2N0), or weak/absent (ypT3-4 or N+). For patients who underwent surgery, the events were local, systemic recurrences and death from the date of surgery for disease-free survival (DFS), recurrences for time to recurrence (TTR), and death from any cause for overall survival (OS). All patients who were managed with the Watch-and-Wait strategy were considered to have clinical complete response (ycTNM0) and were offered a strict surveillance protocol.

[0255] Immunohistochemistry

[0256] Initial biopsies of all patients performed for diagnosis purpose were retrieved from all centers. Two formalin-fixed paraffin-embedded (FFPE) tumor tissue sections of 4 μm were processed for immunochemistry with antibodies against CD3+ (2GV6, 0.4 μg/mL; Ventana, Tucson, Ariz., USA) and CD8+ (C8/144B, 3 μg/mL; Dako, Glostrup, Denmark) according to the previously described protocol (17) revealed with the Ultraview Universal DAB IHC Detection Kit (Ventana, Tucson, Ariz., USA), and counterstained with Mayer's hematoxylin.

[0257] Biopsy-Based Immunoscore (IS.sub.B) Determination

[0258] Digital images of stained tissue sections were obtained with a 20× magnification and a resolution of 0.45 μm/pixel (Nanozoomer H T, Hamamatsu, Japan). Delimitation of the tumoral component excluding normal tissue and low/high grade dysplasia-associated lesions was performed by an experienced pathologist (CL). The mean densities of CD3+ and CD8+ T cells in the tumor region were determined with a dedicated IS module of the Developer XD image analysis software (Definiens, Munich, Germany). The mean and distribution of the staining intensities were monitored providing an internal staining quality control. A final quality check was performed to remove nonspecific staining detected by the software. Determination of IS.sub.B was directly derived from the methodology used to determine the Immunoscore (IS) in the international validation cohort of IS in colon cancers which have shown a strong inter-observer reproducibility (17). CD3+ and CD8+ T cells densities in the tumoral region of each patient were compared to that obtained for the whole cohort of patient and converted accordingly into percentile. Then, the mean of the two percentiles (CD3 and CD8) was translated into one of the three IS.sub.B categories (FIG. 1B): IS.sub.B Low (0-25%), IS.sub.B Intermediate (>25-70%), and IS.sub.B High (>70-100%). The IS.sub.B determination was performed blinded to the study endpoint.

[0259] RNA Extraction and Transcriptomic Analysis by NanoString Technology

[0260] Total RNA from 20 μm FFPE tumor tissue sections from all patients for which both biopsies and the corresponding surgical specimen post-nT was available (cohort 1 and 2; n=62) and from colorectal cancer patients not treated with nT (n=13) was isolated using the RecoverAll™ Total Nucleic Acid Isolation Kit (Ambion ThermoFisher, Monza, Italy). Distribution of tumor extension T and N stages among patients with or without nT did not display any statistical difference. The quality and quantity of the isolated RNA was measured using Agilent RNA 6000 Nano kit (Agilent Technologies, Santa Clara, Calif.) and NanoDrop 2000 (ThermoFisher Scientific, Waltham, USA) and 100-400 ng RNA of each sample was processed using an in-house panel of 44 immune-related genes (Nanostring Technologies, Seattle, Wash., USA). Reporter-capture probe pairs were hybridized and the probe/target complexes were immobilized and counted on the nCounter analyzer. Background subtraction was applied to raw data and normalization based on the geometric mean of positive control and internal housekeeping genes (GUSB, SP2) was performed using the nSolver Analysis software, version 2.5.

[0261] Statistical Analysis and Data Visualization

[0262] Statistical analyses and data visualizations were performed using the R software version 3.5.1 with the add-on survival, survminer, ggpubr, ggplot2, rms and coin packages. The associations between IS.sub.B and clinical characteristics were assessed through the chi-square or Fisher tests of independence. Association level between CD3+ and CD8+ cell densities was measured by Pearson's correlation coefficient r and related P value. Survival univariate analyses were performed using the log-rank test and the Cox proportional hazards model. Survival curves were estimated by the Kaplan-Meier method. The log-rank test for trend from the survminer package was performed to detect ordered differences in survival curves. Multivariate survival analyses were performed with Cox proportional hazards model to test the simultaneous influence of all covariates. The proportional hazards assumption (PHA) for each covariate was tested using the cox.zph function. The relative importance of each parameter to survival risk was assessed by the chi-square from Harrell's rms R package. The association between IS.sub.B and nT ordinal response level was assessed using a unilateral linear-by-linear association test. The associations between nT response levels and CD3+, CD8+ T cells densities and gene intensities were assessed by Kendall's correlation test, T test, and Mann-Whitney U test. Wilcoxon test adjusted to control false discovery rate by using the Benjamini and Hochberg procedure was used to test treatment response level in transcriptional analysis. The ycTNM staging and IS.sub.B were included in the proportional odds ordinal logistic regression model to predict good histopathologic response to nT. P values<0.05 were considered statistically significant. Principal component analysis (PCA) was performed with PCA and fviz_pca_ind functions from packages FactoMineR and factoextra. Linear weighted kappa was used to measure the agreement between resected tumors and biopsy samples in IS calculation.

[0263] Results:

[0264] Biopsy-Based Immunoscore (IS.sub.B) Determination on the Rectal Cancer Diagnostic Tissues

[0265] CD3+ lymphocytes and cytotoxic CD8+ cells were assessed on initial tumor biopsies performed for diagnosis purpose of LARC (n=322) treated by nT. The immunostaining intensity was monitored to ensure a valid detection and counting of stained cells with the image analysis software (not shown). Seven patients were excluded after biomarker quality control (2.8%), and 4 patients were excluded after clinical data quality control (1.2%). The median density of CD3+ and CD8+ T cells in the tumor were 1363 cells/mm.sup.2 and 274 cells/mm.sup.2, respectively (data not shown). The CD3+/CD8+ T cells ratio was highly variable among patients, with a coefficient of determination (r.sup.2) between both markers of 0.58 (data not shown). IS.sub.B was derived from the CD3+ and CD8+ T cells densities (data not shown). CD3 and CD8 densities in the tumor were converted into percentiles referring to the densities observed in all patients. IS.sub.B mean percentile of CD3 and CD8 was calculated for each biopsy (IS.sub.B mean score). No difference for the mean score was observed between the two cohorts (data not shown). After converting the mean score into IS.sub.B scoring system, overall 22.7%, 52.5%, and 24.8% of patients had IS.sub.B Low, Intermediate and High, respectively. Of note, IS.sub.B Intermediate category was more represented in the cohort 2 (61.9%), as compared to cohort 1 (43.5%).

[0266] Biopsy-Based Immunoscore (IS.sub.B) Associated Prognostic Value

[0267] Distribution analysis of IS.sub.B did not display any association with age, sex or tumor location (Table 1). The magnitude and reproducibility of the IS.sub.B prognostic performance were tested in two independent cohorts. In cohort 1 (n.sub.1=131), a significant difference in DFS between patients stratified by IS.sub.B was observed (P test for trend [P.sub.tft]=0.012; HR.sub.[High versus Low]=0.21 (95% CI 0.06-0.78)). Patients with IS.sub.B High were at low-risk of relapse, with the 5-year DFS of 91.1% (95% CI 82.0-100) versus 65.8% (95% CI 49.8-86.9) in patients with IS.sub.B Low. These results were confirmed in second independent cohort (n.sub.2=118; P.sub.tft=0.021; HR.sub.[High versus Low]=0.25, 95% CI 0.07-0.86). Identical results were obtained when removing the 3 patients with UICC-TNM stage I tumors (data not shown). In pooled analysis (n=249), a significant difference between patient's groups stratified by IS.sub.B was evidenced by univariate analysis (data not shown) and illustrated by Kaplan-Meier curves for TTR (P<0.001), DFS (P<0.005), and OS (P=0.04; data not shown).

[0268] Biopsy-Based Immunoscore (IS.sub.B) and Response to Neoadjuvant Treatment

[0269] We investigated if the prognostic value associated to IS.sub.B was at least partly a consequence of a relationship between IS.sub.B and the quality of the nT response. The quality of response to nT is assessed 6 to 8 weeks after nT by imaging (ycTNM) and microscopic examination of the resected tumor, by the Dworak classification, a tumor regression grading system, ypTNM, downstaging and the neoadjuvant rectal (NAR) score. In our cohorts (n=249 patients), high CD3+ and CD8+ T cells densities were significantly associated with a good response to nT evaluated by both Dworak classification and ypTNM staging (all P<0.005; data not shown). The mean of CD3+ and CD8+ percentiles (IS.sub.B mean score) was correlated with the NAR score, Dworak classification, and ypTNM staging (data not shown). The IS.sub.B level and distribution was positively correlated with tumor response to nT (data not shown). IS.sub.B High patients were not found in the non-responder Dworak 0 group, and 52.9% of patients with undetectable tumor cells (ie. the Dworak 4 group) were IS.sub.B High (P=0.0006). The same correlation was observed with the ypTNM, tumor downstaging, and NAR (data not shown). Good responders to nT were six times more frequent in the IS.sub.B High group than in the IS.sub.B Low group according to the NAR scoring system (data not shown). Immune consequences of nT were then investigated on post-nT tumor samples (Dworak 0-4; n=62) by analyzing 44 immune-related genes (data not shown). Gene expression levels were highly variable among patients (data not shown). Unsupervised hierarchical clustering showed that 31.7% (n=19) of patients presented with signs of local immune activation after nT (data not shown). The immune activation status after nT was positively correlated with the densities of CD3+ and CD8+ T cells (i.e. IS.sub.B) before treatment (data not shown). Non-responder tumors (Dworak 0-1) presented similarly low level of immune-related genes expression compared to tumors not treated by nT (data not shown). Patients with a partial/complete response to neoadjuvant treatment had a significantly higher expression of genes associated with adaptive immunity (CD3D, CD3E, CD3Z, CD8A), Th1 orientation (TBX21 Tbet, STAT4), activation (CD69), cytotoxicity (GZMA, GZMH, GZMK, PRF1), immune checkpoints (CTLA-4, LAG3), and chemokines (CCL2, CCL5, CX3CL1), as compared to patients non-responders to nT (data not shown). This suggests a link between the quality of the natural adaptive cytotoxic immune response (IS.sub.B), the presence of a post-nT immune activation and the degree of response to nT. Gene expression data analysis through a Principal Component Analysis (PCA) visualization further reinforced the putative link existing between the response to nT and the immune environment by showing distinct patterns of gene expression depending on the degree of response to nT (data not shown). “The combination of the second and third dimension was the most accurate to discriminate responders/non-responders.

[0270] Biopsy-Adapted Immunoscore (IS.sub.B)—a Biomarker to Optimize Patient Care

[0271] We investigated whether the IS.sub.B could provide valuable prognostic information when combined with clinic and pathologic criteria available (i) before nT (i.e. initial imaging, cTNM (UICC TNM 8.sup.th edition)), (ii) after nT (ie. imaging post-nT, ycTNM) and (iii) after surgery (pathologic examination, ypTNM). In Cox multivariate analysis, IS.sub.B was a stronger predictive marker of DFS than other clinicopathological parameters including cTNM (IS.sub.B High versus IS.sub.B Low: HR=0.2, P<0.001) and ycTNM (IS.sub.B High versus IS.sub.B Low: HR=0.25, P=0.039). IS.sub.B further remained a significant independent parameter associated with DFS when combined to ypTNM (Table 4). It is known that the accuracy of the complete response post-nT defined by imaging is imperfect. Thus, only 25 to 50% of clinical complete responders have no residual tumor (i.e. complete histologic response) (22-24). IS.sub.B combined to imaging post-nT (ycTNM) increased the accuracy of prediction of histological good responders (ypTNM 0-I) as compared to ycTNM alone. Three out of 32 patients with good response to nT (ycTNM=0-I, n=32) experienced distant relapses, and no local relapse were observed. Importantly, no relapse was observed in IS.sub.B High patients (FIGS. 1A,B, 2A,B and 3). Thus, IS.sub.B could help to select patients who could achieve a very favorable outcome and be eligible to a Watch and Wait strategy.

[0272] IS.sub.B in Patients Managed with Watch-and-Wait Strategy

[0273] In a series of patient treated by Watch-and-Wait strategy (n=73), we retrieved the initial diagnostic biopsies to evaluate the IS.sub.B and the associated clinical outcome. Overall, 23%, 51%, and 26% were classified as IS.sub.B High, IS.sub.B Intermediate, and IS.sub.B Low, respectively. Time to relapse was significantly different among patients stratified for IS.sub.B (P.sub.[High versus Low]=0.025; data not shown). No evidence of relapse was noticed during the follow-up period in IS.sub.B High patients. Under the Cox proportional hazards regression model, the 5-year probability of survival without recurrence ranged from 46% to 89% according to IS.sub.B Mean Score (data not shown). In Cox multivariable analysis, IS.sub.B was related to the patient's TTR, independent of age, tumor location, and the cTNM classification (UICC TNM 8.sup.th edition) (P.sub.[High versus Low]=0.04; data not shown).

DISCUSSION

[0274] This work highlights the links between (i) the quality of natural intra-tumor immunity evaluated by the IS.sub.B (ii) the intensity of in situ immune reaction post-nT (iii) the extend of the tumor regression post-nT and (iv) the clinical impact in terms of prevention of tumor recurrence and survival. From a clinical point of view, IS.sub.B provides a reliable estimate of both the quality of response after nT and of the risk of recurrence and death in LARC patients. IS.sub.B combined with imaging, could further identify patients with a complete clinical response whom can benefit from a close surveillance strategy post-nT, thus avoiding a disabling and useless rectal amputation surgery.

[0275] IS.sub.B can be performed on routine diagnosis biopsies without any additional medical procedure. The rigorous and standardized quantification of immune cell infiltrates was achieved as for the IS colon study (17).

[0276] In the current study, IS.sub.B was positively and significantly correlated with tumor response to nT. This observation is consistent with our previous preliminary result (18) and with studies using an optical semi-quantitative evaluation of immune cell infiltrates (19,20,25). In the IS.sub.B Low group (22.7% of the cohort), only 5% of patients experienced complete response (Low NAR score), suggesting that an optimization or modification of nT such as adjunctive therapies (26), immunotherapy (27), or drug repositioning may provide greater benefits for these patients in order to achieve a better response. We evidenced an association between signs of in situ cytotoxic adaptive immune response and inflammatory interferon type I-associated molecules production post-nT and the response to treatment. Type I IFNs play a key role in antitumoral immunity by promoting the maturation and presentation capacity of dendritic cells and their migration to lymph nodes (28). This immune state was influenced by the quality and the intensity of the natural immune response preexisting before nT. IS.sub.B High could not only favor nT-dependent tumor cell death, but also promote the presence of resident immune components that could be essential to avoid local recurrences in organ preservative strategies such as Watch-and-Wait. Of note, few IS.sub.B high patients did not achieve a good response, highlighting that treatment resistance is also guided by independent tumor intrinsic factors (29) or the presence of a suppressive microenvironment (30). Neoadjuvant treatment with development of clinical complete response post-nT has raised the possibility of organ-preserving strategies, because radical resection of the rectum results in functional outcomes, immediate morbidity, and even mortality rates (31). However, imaging after nCRT (ycTNM) has low accuracy in predicting pathologic complete response due to over or under-staging (32). Importantly, no relapse was observed in good responders with IS.sub.B High patients. In addition, IS.sub.B increased the accuracy prediction for very good responders (ypTNM 0-I) evaluated by imaging and identified a subgroup of patients treated with an organ-preserving strategy (Watch-and-Wait) with a very favorable outcome. No biomarker is currently available to help selection of good responders eligible to Watch-and-Wait strategy (9). These results may have significant implication in selecting potential candidates for organ-preservation including patients with IS.sub.B High and complete clinical response to nT, but also those with a delayed complete clinical response (i.e. “nearly-complete responders”) that are presently classified as incomplete responders (33). This study has some limitations. The immune densities associated with predefined cut points (i.e. 25.sup.th and 70.sup.th percentile) are closely linked to the clinical characteristics of the studied cohort. The densities used as cut point are relevant to LARC patients treated by nT before surgery. In addition, assessment of IS.sub.B was performed on initial biopsies; this implies analysis of only a small fraction of the tumor (10-15% of the surface of cut from a tumor block available after TME) and no analysis of the invasive margin not present on biopsies. In order to evaluate the correspondence of IS.sub.B and IS in resected tumor, we analyzed 33 colon cancer biopsies and their associated resected tumor, we found a partial correlation between these two specimens (data not shown, kappa=0.45, p=0.0004). All discrepancies were only observed between 2 consecutive categories of IS. Despite this limited surface analysis and the absence of invasive margin, the prognostic value of the IS.sub.B was retained suggesting the accuracy of the immune evaluation on initial diagnostic biopsy when the surgical piece is unavailable or is impossible to analyze due to architectural changes secondary to the neoadjuvant treatment. In addition, performing IS on post-operative specimen would not allow an assessment of its predictive value of the response to nT. Furthermore, due to the deep histological modifications after nT (no clear delimitation of the tumor and its invasive margin) an IS on post nT specimen is not feasible. The study was performed on patients who came from different countries and received standard-of-care treatment in real-life clinical practice. Despite the size of the specimen and the multiple types of patient care, the strong and constant prognosis value associated with IS.sub.B, highlight the robustness of the test, and its generalizability. Prognostic parameters such as mismatch repair, KRAS, and BRAF status not available in our study, were not included in multivariate analysis with IS scoring system. However, MSI+ cases are rare in rectal cancer (<5%) (34), and we recently evidenced that IS was an independent prognostic parameter for survival when associated with MSI, KRAS and BRAF status in colonic cancers (35). Most of the rectal cancer included in this study was adenocarcinomas. A sub-analysis by histologic subtypes could not be performed due to the large multicentric character of the cohorts studied, with heterogeneous level of histopathological description and the obvious small effective of mucinous carcinomas, signet ring cell carcinoma, or tumor budding to address their relative prognostic impact with enough power. This study emphasizes the importance of the initial diagnostic biopsies, often done in private practices, and not easily available in some cases. Rectal cancer patients would benefit from a close partnership between private pathology practices, clinics, and teaching hospitals in order to initially assess their immune status (IS.sub.B). This material could become in the near future essential and be part of the personal medical file of rectal cancer patient as it is the sole material available before any neoadjuvant treatment. IS.sub.B may facilitate a personalized multimodal treatment of rectal cancer particularly in patients with IS.sub.B High tumors at baseline and with signs of tumor regression by imaging. These patients should benefit the most from the conservative strategy and in turns preserve their quality of life.

[0277] In conclusion, our results indicate that IS.sub.B could be used (i) to predict tumor response after nT (ii) to re-stage local disease after nT, and (iii) to predict clinical outcome. This method may facilitate a personalized multimodal treatment of rectal cancer particularly in patients with IS.sub.B High tumors at baseline and with signs of tumor regression by imaging. These patients should benefit the most from the conservative strategy and in turns preserve their quality of life. IS.sub.B is yet to be validated on larger Watch-and-Wait cohorts both retrospectively and prospectively. Such validations are planned in international collaboration studies using the International Watch-and-Wait Database and in the OPERA ongoing clinical trial (NCT02505750).

TABLE-US-00001 TABLE 1 Clinical characteristics of patients who underwent total mesorectal excision according to IS.sub.B Cohort 1 Cohort 2 IS.sub.B Low IS.sub.B Int IS.sub.B High IS.sub.B Low IS.sub.B Int IS.sub.B High Characteristics No. (%) No. (%) No. (%) P No. (%) No. (%) No. (%) P No. of patients Age 0.58* 0.12* ≤65 years 12 (40) 24 (44.4) 21 (52.5) 15 (60) 28 (38.4) 11 (55)  >65 years 18 (60) 30 (55.6) 19 (47.5) 10 (40) 45 (61.6) 61.6 (9) Gender 0.79* 0.10* Male 18 (60) 36 (66.7) 27 (67.5) 18 (72) 51 (69.9) 9 (45) Female 12 (40) 18 (33.3) 13 (32.5) 7 (28) 22 (30.1) 11 (55) Tumor location 0.92* 0.59* Inferior 15 (50) 28 (51.9) 23 (57.5) 14 (56) 33 (45.8) 10 (50) Middle 10 (33.3) 18 (33.3) 10 (25) 10 (40) 34 (47.2) 7 (35) Superior 5 (16.7) 8 (14.8) 7 (17.5) 1 (4) 5 (6.9) 3 (15) cTMM stage 0.08† 0.03† I 1 (3.3) 1 (1.9) — — — 1 (5) II 14 (46.7) 21 (38.9) 9 (22.5) 5 (20) 9 (12.3) 7 (35) III 15 (50) 32 (59.3) 21 (77.5) 20 (80) 64 (87.7) 12 (60) ycTNM stage 0.36† 0.04† 0 1 (4.3) — 3 (8.3) — — — I 2 (8.7) 9 (22.5) 4 (11.1) 3 (16.7) 6 (12.8) 4 (57.1) II 15 (65.2) 18 (45) 19 (52.8) 3 (16.7) 8 (17) 1 (14.3) III 5 (21.7) 12 (30) 10 (27.8) 8 (44.4) 31 (66) 2 (28.6) IV — 1 (2.5) — 4 (22.2) 2 (4.3) — ypTNM stage 0.69† 0.05† 0 2 (67) 5 (9.4) 5 (12.5) — 1 (1.4) 3 (15) I 5 (16.7) 15 (28.3) 13 (32.5) 4 (17.4) 20 (28.2) 8 (40) II 11 (36.7) 17 (32.1) 14 (35) 9 (39.1) 23 (32.4) 5 (25) III 11 (36.7) 14 (26.4) 8 (20) 6 (26.1) 24 (33.8) 4 (20) IV 1 (3.3) 2 (3.8) — 4 (17.4) 3 (4.2) — Dworak 0.36† 0.05† classfication 0 — 3 (6) — 2 (10) 6 (10.2) — 1 7 (25.9) 7 (14) 4 (10.5) 9 (45) 21 (35.6) 2 (20) 2 14 (51.9) 19 (38) 19 (50) 6 (30) 21 (35.6) 3 (30) 3 4 (14.8) 16 (32) 10 (26.3) 3 (15) 10 (16.9) 1 (10) 4 2 (7.4) 5 (10) 5 (13.2) — 1 (1.7) 4 (40) NOTE *Chi square P value for independence between clinical variables and IS.sub.B level †Fisher's test P value for independence between clinical variables and IS.sub.B level — not applicable

TABLE-US-00002 TABLE 2 Clinical characteristics of patients who underwent the Watch-and-Wait strategy according to IS.sub.B. Overall IS.sub.B Low IS.sub.B Int IS.sub.B High Characteristics No. (%) No. (%) No. (%) No. (%) P No. of patients 73 (100) 19 (26) 37 (50.7) 17 (23.3) — Age 0.28* ≤65 years 32 (43.8) 6 (31.6) 16 (43.2) 10 (58.8) >65 years 41 (56.2) 13 (68.4) 21 (56.8) 7 (41.2) Gender 0.32* Male 40 (54.8) 10 (52.6) 23 (62.2) 7 (41.2) Female 33 (45.2) 9 (47.4) 14 (37.8) 10 (58.8) Tumor location 0.04† Inferior 43 (81.1) 15 (100) 20 (80) 8 (61.5) Middle 9 (17) 0 (0) 5 (20) 4 (30.8) Superior 1 (1.9) 0 (0) 0 (0) 1 (7.7) cTNM stage 0.02† I 9 (17.3) 2 (14.3) 7 (28) 0 (0) II 10 (192) 6 (42.9) 2 (8) 2 (15.4) III 33 (63.5) 6 (42.9) 16 (64) 11 (84.6) *Chi square P value for independence between clinical variables and IS.sub.B level †Fisher’s test P value for independence between clinical variables and IS.sub.B level — Not applicable

TABLE-US-00003 TABLE 3 Median survival [+/− IQR] and event numbers  elapse Relapse or OS (months) Death Nb. TTR/DFS (months) N  Death Nb. All 45.4 (25.7-65.5) 55 38.5 (16.4-58) 60 79 cohort 1 55 (32.3-91.3) 22 46.4 (23.7-81.7) 23 30 cohort 2 36.9 (18.6-48.3) 33 32.5 (10.4-47.7) 37 49 W&W 37.1 (24.2-59.2) 15 31.5 (20.3-45.6) 14 22 indicates data missing or illegible when filed

TABLE-US-00004 TABLE 4 Multivariate Cox models for disease-free survival according to biopsy-adapted Immunoscore (IS.sub.B) combined with available clinical parameters Before neoadjuvant treatment After neoadjuvant treatment After surgery PHA HR P PHA HR P PHA HR P Characteristics test (95% CI) value* test (95% CI) value* test (95% CI) value Age Under vs Over 65 years 0.922 1.38 (0.85-2.24) 0.19 0.432 1.41 (0.69-2.9) 0.346 0.636 1.46 (0.86-2.48) 0.159 Tumor location Middle vs Inferior 0.43 1.1 (0.67-1.8) 0.72 0.688 0.9 (0.45-1.81) 0.766 0.894 0.83 (0.47-1.46) 0.527 Superior vs Inferior 0.5 0.66 (0.26-1.69) 0.39 0.583 0.3 (0.04-2.24) 0.24  0.212 0.74 (0.29-1.9) 0.529 Sex Male vs Female 0.06 1.54 (0.9-2.63) 0.118 0.131 1.87 (0.8-4.37) 0.148 0.033 1.38 (0.76-2.49) 0.291 Immunoscore (IS.sub.B) Intermediate vs Low 0.476 0.65 (0.38-1.1) 0.111 0.906 0.76 (0.33-1.73) 0.508 0.708 0.93 (0.5-1.71) 0.807 High vs Low 0.83 0.2 (0.08-0.49) <0.001 0.834 0.25 (0.07-0.93) 0.039 0.209 0.34 (0.13-0.89) 0.028 cTNM stage III vs I-II 0.59 1.18 (0.68-2.04) 0.56 — — — — — — ycTNM stage 0 vs III — — — — — — — — — I vs III — — — 0.916 0.62 (0.23-1.69) 0.349 — — — II vs III — — — 0.257 0.48 (0.22-1.08) 0.076 — — — ypTNM stage 0 vs III — — — — — — 0.208 0.14 (0.02-1.01) 0.051 I vs III — — — — — — 0.071 0.2 (0.09-0.45) <0.00 II vs III — — — — — — 0.207 0.51 (0.29-0.89) 0.018 *The significance of the multivariate Cox regression model was evaluated with the Wald test — not applicable IS, Immunoscore; PHA, proportional hazards assumption; HR, Hazard ratio indicates data missing or illegible when filed

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