Virtual Library
Start Your Search
Nuria Viñolas
Author of
-
+
FP12 - Tumor Biology and Systems Biology - Basic and Translational Science (ID 188)
- Event: WCLC 2020
- Type: Posters (Featured)
- Track: Tumor Biology and Systems Biology - Basic and Translational Science
- Presentations: 1
- Moderators:
- Coordinates: 1/28/2021, 00:00 - 00:00, ePoster Hall
-
+
FP12.09 - Molecular Insight into NADIM Clinical Trial: Potential Immune Biomarkers of Pathological Response for NSCLC Patients. (ID 3552)
00:00 - 00:00 | Author(s): Nuria Viñolas
- Abstract
- Presentation
Introduction
Many studies have demonstrated that chemo-immunotherapy is a promising approach for NSCLC patients but still exists a lack of prediction biomarkers of survival. We have recently showed that pathological response is a surrogate of progression free survival (PFS) including infiltrating immune cells as potential biomarker of pathological response in NADIM clinical trial (Provencio et al., 2020. Lancet Oncology, in press).
New biomarkers in peripheral blood are being described, focused on the immune system response. Preliminary data was presented at WCLC 2019 however additional results are included in this report. Here we describe the effect of chemo-immune neoadjuvant treatment on resectable NSCLC stage III patients’ immune system and describe blood biomarkers that could help to identify responders to this combination therapy.
Methods
Peripheral mononuclear cells (PBMCs) and plasma from NADIM clinical trial patients before and after chemo-immune neoadjuvant treatment were used. Phenotyping and activation levels of immune cell populations were analyzed by flow cytometry, focused on CD4 T cells, CD8 T cells, T cells NK like and NK cells. Moreover, characterization of the immune response was evaluated by a cytokine array.
Clinical evaluation of pathological response, classified patients in 3 groups, complete (CPR, 0% tumor cells), major (MPR, <10% viable tumor) and incomplete (IPR, >10% viable tumor). Wilcoxon and Kruskall-Wallis statistic tests were used.
Results
Even though we have previously described a decrease of T lymphocytes on tissue after treatment, we do not see these changes on blood. Thus, percentages of PBMCs (T cells, B cells, NK cells and macrophages) did not vary after neoadjuvant treatment. However, lower levels of activated CD4 T cells and NK cells were observed. Interestingly, this decrease was exclusively statistically significant for patients who achieved a CPR, but no differences were observed for MPR or IPR. As expected, detection of PD1+ cells after neoadjuvant Nivolumab (anti-PD1) treatment was almost completely abrogated, however, a trend for higher PD1+ cell proportions was observed in patients achieving CPR at diagnosis.
Furthermore, many cytokines involved in immune response and described as putative biomarkers for immunotherapy in NSCLC as IL-2, IL-15, IL-6, IL-13 or IFN-gamma, among others, were decreased after neoadjuvant treatment. Notably, stratifying by pathological responses, this decrease was statistically significant only for non-complete responses.
Conclusion
The analysis of immune cell markers on blood samples could be a source for potential surrogate markers of pathological response to neoadjuvant treatment on NSCLC patients.
Similarly, to what occurs in tissue, CPRs showed differences compared to MPR or IPR in some blood markers, both at the cellular and cytokine level. Thus, after treatment, patients achieving CPRs do not seem to reduce their levels of cytokines such as IL-2, IL-15, IL-6, IL-13 or IFN-g associated with anti-tumor response, but they do reduce their levels of activated CD4 and NK cells
Only Members that have purchased this event or have registered via an access code will be able to view this content. To view this presentation, please login, select "Add to Cart" and proceed to checkout. If you would like to become a member of IASLC, please click here.
-
+
MA03 - New and Revisited Prognostic Factors in Early Stage Lung Cancer (ID 119)
- Event: WCLC 2020
- Type: Mini Oral
- Track: Early Stage/Localized Disease
- Presentations: 1
- Moderators:
- Coordinates: 1/29/2021, 15:30 - 16:30, Scientific Program Auditorium
-
+
MA03.08 - Impact of COVID-19 Pandemic in the Diagnosis and Prognosis of Lung Cancer (ID 3700)
15:30 - 16:30 | Author(s): Nuria Viñolas
- Abstract
- Presentation
Introduction
COVID-19 pandemic has drastically changed the management of patients with cancer. The prioritization of the healthcare towards COVID-19 patients could interfere with the initial diagnosis, resulting in delayed treatment and worse outcome. We aimed to study the incidence of lung cancer new diagnosis, severity and clinical outcomes during Covid-19-period (during-COVID) compared to the same period in 2019 (before-COVID).
Methods
Bicenter retrospective cohort study of newly diagnosed non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC) patients before (Jan-Jun/19) and during COVID-19 (Jan-Jun/20) in Spain. Clinical data were collected. We primarily assessed the difference on new lung cancer cases between both periods, and the disease severity considering: Performance status (PS), stage and any significant complication at diagnosis. Secondarily, we assessed the 30 days-mortality rate, progression-free survival (PFS) and overall survival (OS) by period.
Results
162 newly diagnosed lung cancer patients (68% NSCLC and 32% SCLC) were enrolled, with median age of 66 years, 70% were male, 33% smokers, 25% with PS ≥2. Advanced disease was diagnosed in 50% of NSCLC and 61% SCLC; 13% of NSCLC harbored driver alterations.
During-COVID, the number of new cases diagnosed decreased by 38% (43 NSCLC; 19 SCLC), compared to before-COVID period (67 NSCLC; 33 SCLC). More symptomatic cases were new diagnosed during vs. before-COVID. The Table 1 summarized clinical data and complications of new lung cancer cases by period and histology.
In NSCLC population diagnosed during-COVID, we observed more respiratory symptoms at diagnosis (30% vs. 23% before-COVID) with mainly locally-advanced/advanced disease (82% vs. 76% before-COVID). Among the cases hospitalized, the mortality during-hospitalization was 44% (2/9) vs. 17% before-COVID.
In SCLC population diagnosed during-COVID, respiratory symptoms were more common (32% vs. 24% before-COVID), but no more aggressive disease observed in terms of stage, complications and hospitalizations. Among the 4 cases hospitalized at diagnosis, none died during-hospitalization vs. 18% before-COVID (2/11).
Overall, during-Covid the mOS was 6.7 months [95% CI, 5.4-not reached] vs. 7.9 months [95% CI, 4.7-12] before-COVID. In NSCLC, the 30-days mortality was 49% vs. 25% before-COVID; in SCLC, it was 32% vs. 18% before-COVID. Updated data and treatment outcomes will be presented in the meeting.
Conclusion
Lung cancer diagnosis has been affected during the COVID-19 pandemic with fewer cases diagnosed and more symptomatic disease compared to 2019, which seems to be associated with worse outcomes. This study is still ongoing.
Only Members that have purchased this event or have registered via an access code will be able to view this content. To view this presentation, please login, select "Add to Cart" and proceed to checkout. If you would like to become a member of IASLC, please click here.
-
+
P09 - Health Services Research/Health Economics - Real World Outcomes (ID 121)
- Event: WCLC 2020
- Type: Posters
- Track: Health Services Research/Health Economics
- Presentations: 2
- Moderators:
- Coordinates: 1/28/2021, 00:00 - 00:00, ePoster Hall
-
+
P09.15 - Severity of Lung Cancer Disease in Hospitalized Patients During COVID-19 (ID 3373)
00:00 - 00:00 | Author(s): Nuria Viñolas
- Abstract
Introduction
Covid-19 pandemic has drastically changed the management of patients with cancer; however, there is still limited data regarding the real impact of Covid-19 on patient’s outcomes due to delayed diagnosis and treatment of clinical complications. We aimed to assess the prevalence, severity and mortality of clinical complications and oncology emergencies in hospitalized patients in our institution during the Covid19 period vs. the same period of 2019.
Methods
We conducted a retrospective study of patients with small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC) who were admitted to the Department of Medical Oncology during Jan-Jun 2019 (before-Covid) and Jan-Jun 2020 (Covid-19 period). Clinical, pathological and biological data were collected. We assessed the clinical severity in both periods including: PS at admission, progression disease (PD), oncologic emergencies (%), start of a systemic therapy or switch to other therapy line. We also analyzed the differences on the 30-day mortality rate since hospitalization between both periods.
Results
229 admissions, 133 during and 93 before Covid-19 pandemic (N=180 patients) were enrolled; the median duration of the hospitalization was 9 days (4-16). Median age was 66 years, 35% were female, 88% with PS≥2, 27% were current smokers; 83% had NSCLC histology. Most of them (82%) had advanced disease at admission; 69% were under systemic therapy (chemotherapy 39%, immunotherapy 17%, targeted therapies 11%). Nine patients (4%) were active covid-19 cases (9 NSCLC, 0 SCLC).
The table 1 summarized the most common clinical conditions by histology, in both periods.
In NSCLC population, during-Covid, lower rate of admissions were observed (4 cases less per month), with no increase of oncologic emergencies. The PD during hospitalization was slightly higher during vs. before-Covid, but no differences were observed in 30-days mortality rate.
In SCLC population, during-Covid, the rate of admissions was doubled (2 cases more per month), with more cases progressing during the hospitalization. (46% during vs. 34% before-Covid). In contrast to NSCLC, the 30-days mortality rate was higher during-Covid (38%) vs. before-Covid (20%). Updated data will be presented in the meeting.
NSCLC (N= 190) SCLC (N= 39) During-Covid (2020)
N=83 (44%)
Before-Covid (2019)
N=107 (52%)
During-Covid (2020)
N=13 (33%)
Before-Covid (2019)
N=26 (67%)
Baseline characteristics Main reason of hospitalization
Dyspnea
Fever
Pain
Neurological symptoms
Others27 (33%)
20 (24%)
9 (11%)
11 (13%)
16 (19%)26 (24%)
22 (21%)
16 (15%)
20 (17%)
23 (23%3 (23%)
3 (23%)
1 (8%)
4 (30%)
2 (16%)11 (42%)
2 (8%)
1 (4%)
6 (23%)
6 (23%)PS at admission
0-1
≥21 (1%)
82 (99%)22 (21%)
82 (79%)0 (0%)
13 (100%)3 (12%)
23 (88%)Stage at admission
Locally
Locally advanced
Advanced7 (8%)
7 (8%)
69 (84%)7 (7%)
9 (8%)
90 (85%)0 (0%)
4 (30%)
9 (70%)2 (8%)
4 (15%)
20 (77%)N# mets. Sites at admission
≤2
>255 (67%)
28 (33%)64 (60%)
43 (40%)8 (62%)
5 (38%)14 (54%)
12 (46%)Line of therapy (only advanced disease)
0-1
≥255 (65%)
28 (35%)69 (64%)
38 (36%)10 (76%)
3 (23%)21 (81%)
5 (19%)
Disease severity N# Admissions N= 83
(14 per month)N=107
(18 per month)N=26
(4 per month)N=13
(2 per month)N# Readmissions 21 (25%) 22 (21%) 1 (8%) 5 (19%) Median duration of hospitalization (range) 8(1;47)
10(1;104)
8(1;22) 9(1;67)
Oncology Emergencies
Yes
No8 (10%)
75 (90%)22 (20%)
85 (80%)
1 (8%)
12 (92%)7 (27%)
19 (73%)Progression during hospitalization
Yes
No
32 (39%)
51 (61%)35 (32%)
72 (68%)6 (46%)
7 (54%)9 (34%)
17 (66%)Early death (30-days mortality rate)
Yes
No20 (24%)
63 (76%)22 (21%)
84 (79%)5 (38%)
8 (62%)5 (20%)
20 (80%)
Conclusion
We preliminary observed more aggressive disease with worse outcomes in patients with SCLC hospitalized during-Covid compared to the same period in 2019. No differences were observed in NSCLC. The final outcomes will be assessed in a larger and mature cohort still ongoing.
-
+
P09.28 - Access to Intermediate and Intensive Care for Patients With Lung Cancer During the COVID-19 Period (ID 3419)
00:00 - 00:00 | Author(s): Nuria Viñolas
- Abstract
Introduction
COVID-19 pandemic has dramatically impacted the health national systems, interfering with the access to standard care of other illnesses. However, the real impact of COVID-19 crisis on the cancer care remains unknown. We assessed the access to invasive procedures and critically ill patient units (intensive and intermediate care) in patients with lung cancer hospitalized during pandemic period (during-Covid) compared to the same period in 2019 (before-Covid).
Methods
Single-center retrospective study of lung cancer patients hospitalized before (Jan-Jun.2019) and during-Covid (Jan-Jun.2020). Clinical data, access to care and interventions were collected. Patients were also classified in 3 groups according to an estimated life expectancy (based on stage, histology, molecular profile and line-therapy): favorable group (FG) with median (m) overall survival (OS) >5 years, intermediate (IG) 1-5 years and poor (PG) <1 year. We primarily compared the number of admissions to intensive and intermediate-unit care (ICU and intermCU respectively), between both periods, and then stratified by prognostic group. We also assessed the invasive procedures in each period.
Results
229 admissions were registered (N=180 patients). Median age was 66 years, 64% were male, 67% with Performance status ≥2; 83% had non-small cell lung cancer and median length of stay was 9 days (1-104). Most of them (82%) had advanced disease; 63% were under systemic therapy. By prognostic groups: 17 patients were considered FG (7%), 161 as IG (70%) and 51 as PG (22%). Nine patients were admitted due to active COVID-19 infection.
The table 1 summarized the clinical characteristics and interventions in both periods.
During-Covid, only 2% (n=2) of patients was admitted in ICU vs. 6% (n=8) before-Covid, although, no differences were observed in access to intermCU. The number of invasive interventions was also lower (15%, n=15) vs. before-Covid (33%, n=43).
By prognostic: 20% of patients in FG (n=2) and 9% in IG (n=6) were admitted to ICU/intermCU during Covid vs. none FG cases and 9% in IG (n=8) before-Covid. In contrast, in the PG lower admissions were observed during-Covid (6%, n=1) vs. before-Covid (20%, n=7)
With a mOS since date of hospitalization of 3.3 months (95% CI 2.6-4.8), the 30-days-mortality rate was 23% overall; slightly higher during (26%) vs. before-Covid (20%). Updated data will be presented in the meeting.
ConclusionDuring-Covid
(2020)
(N, %)
Before-Covid
(2019)
(N, %)
Baseline characteristics
Admissions
N=96
(16 per month)
N=133
(21 per month)
Sex
Female
Male
42 (44%)
54 (56%)
40 (30%)
93 (70%)
Age
<65 years
>65 years
48 (50%)
48 (50%)
59 (44%)
74 (56%)
Performance Status at admission
0-1
≥2
1 (1%)
95 (99%)
25 (19%)
105 (81%)
Stage at admission
Locally
Locally advanced
Advanced
9 (9%)
13 (14%)
74 (77%)
8 (6%)
11 (8 %)
114 (86%)
Number of metastasis sites at admission
≤2
>2
69 (72%)
27 (28%)
72 (54%)
61 (46%)
Line of therapy (only advanced disease)
0-1
≥2
65 (68%)
31 (32%)
90 (68%)
43 (32%)
Prognostic groups
Favorable (FG)
Intermediate (IG)
Poor group (PG)
10 (10%)
70 (73%)
16 (17%)
7 (5%)
91 (69%)
35 (26%)
Access to care
Intermediate Care
Yes
No
7 (7%)
89 (93%)
7 (5%)
126 (95%)
Invasive Care
Yes
No
2 (2%)
94 (98%)
8 (6%)
125 (94%)
N# Invasive interventions
(e.g. pleural, pericardial punction…)
14 (14%)
38 (29%)
Elective procedures
1 (1%)
5 (4%)
The access to critically ill patient units and invasive interventions for lung cancer patients seems to have been affected during-Covid vs. same period in 2019. The impact on outcomes will be assessed in a larger cohort ongoing.
-
+
P60 - Tumor Biology and Systems Biology - Basic and Translational Science - Immune Bio (ID 198)
- Event: WCLC 2020
- Type: Posters
- Track: Tumor Biology and Systems Biology - Basic and Translational Science
- Presentations: 2
- Moderators:
- Coordinates: 1/28/2021, 00:00 - 00:00, ePoster Hall
-
+
P60.07 - TMB and Selected Mutations in Resectable Stage IIIA NSCLC Patients Receiving Neo-Adjuvant Chemo-Immunotherapy from NADIM Trial (ID 2142)
00:00 - 00:00 | Author(s): Nuria Viñolas
- Abstract
Introduction
Tumor Mutational Burden (TMB) assessment and identification of specific mutations associated to anti-PD1 blockade therapy resistance have become a novel approach to predict the clinical benefit to anti-PD1/PDL1 therapy. However, the clinical relevance of these parameters in terms of pathological response and PFS in neo-adjuvant chemo-immunotherapy has not been established. To answer this question we analysed samples from the NADIM study (NCT03081689), in which resectable stage IIIA NSCLC patients were treated with neoadjuvant chemo-immunotherapy with Nivolumab.
Methods
Pretreatment TMB, defined as the number of nonsynonymous variants (missense and nonsense single nucleotide variants (SNVs)), plus insertion and deletion variants (INDELs) detected per megabase (Mb) of exonic sequence, was estimated from 27 patients that had enough diagnostic material for next generation sequencing using the Oncomine Tumor mutation Load assay (ThermoFisher) following manufacturer’s instructions. The panel covers 1.7 Mb of 409 genes with known cancer associations. Regarding pathological responses, patients were classified into 3 groups: pathologic complete response (pCR) (0% viable tumour at any localization tested), major pathologic response (MPR, <10% viable tumour) and pathologic incomplete response (pIR) (>10% of viable tumour). At data analysis, median follow-up time was 22.7 months.
Results
Median TMB was 5.89 (range 1.68 – 73.95). No differences in TMB value between histologies (adenocarcinoma vs squamous cell), smoking status (former vs current), age or sex were observed. Somatic mutations were identified in lung cancer driver genes such as TP53, KRAS, EGFR, CDKN2A, NOTCH1, BRAF and in specific genes associated with resistance to immunotherapy such as STK11, KEAP1, and RB1. No genomic alterations in ALK, ROS1, PTEN or ERBB2 were found.
Based on literature, a poor prognosis mutation signature (presence of EGFR, STK11, KEAP1 or RB1 mutations) was generated. A third of the sequenced patients (9/27) harboured at least one mutation in one of these genes.
Pathological response data was available from 23 out of 27 patients sequenced. Both the TMB value and the presence of these resistance mutations were not associated with the degree of pathological response.
Regarding PFS, TMB alone was not predictive of disease progression using different thresholds. However, the presence of these resistance mutations was associated with shorter PFS (log-rank p-value=0.032). The median PFS for mutated patients was 21.4 months (95% CI 16-26 months) while median PFS was not reached in non-mutated patients.
Additionally, the combination of this mutational signature with TMB (absence of resistance mutations and TMB-Higher than median) was able to distinguish patients that strongly benefit from this therapy. Although the median PFS was not reached in both groups yet, statistically significant differences were observed (log-rank p-value=0.046). PFS at 18 and 24 months was 100% (95% CI not estimable) for Non-mutated patients with TMB-High vs 70% (95% CI 50-89%) and 58% (95% CI 35-81%) for the rest of patients (mutated patients plus Non-mutated patients with TMB-Low).
Conclusion
TMB did not predict benefit from chemo-immunotherapy induction in our cohort. However, the presence of EGFR/STK11/KEAP1/RB1 mutations alone, or in combination with TMB, may help identify patients that unlikely benefit from neo-adjuvant chemo-immunotherapy
-
+
P60.11 - TCR Repertoire Predicts Pathological Response in NSCLC Patients Receiving Neoadjuvant Chemoimmunotherapy from NADIM Trial (ID 3417)
00:00 - 00:00 | Author(s): Nuria Viñolas
- Abstract
Introduction
Characterization of the T-cell receptor (TCR) repertoire has become a novel approach to monitor immunotherapy responses, however there is lack of knowledge about its clinical relevance as predictive biomarker of pathological response in neoadjuvant chemoimmunotherapy. For this purpose, we analysed samples from the NADIM study (NCT03081689), in which resectable stage IIIA NSCLC patients were treated with neoadjuvant Paclitaxel + Carboplatin + Nivolumab for 3 cycles, achieving a 63% of complete pathologic responses (CPR). PD-L1 TPS and TMB as CPR biomarkers showed AUC ROC of 0.77 and 0.55, respectively, reinforcing the need for new biomarkers (Provencio, M. et al. 2020).
Methods
TCR repertoires from primary tumours or lymph nodes of 19 NSCLC patients were obtained, at both time points: diagnosis and after neoadjuvant treatment. TCR repertoire was analysed in terms of convergence, diversity, evenness and clonal space, defined as the summed frequency of clones belonging to a frecuency group (top 1%, top 1% to 2%, 2% to 5%, and >5%) relative to the total T-cell repertoire. The results were correlated with pathological response groups and ROC curve analysis was performed to test if TCR repertoire-derived parameters could identify patients with CPR.
Results
There were no statistically significant differences observed in TCR repertoire in biopsy samples in terms of diversity (p = 0,797) or convergence (p = 0,202) between the three pathological response groups or between biopsy and surgery samples. However, we observed differences in terms of evenness in biopsy samples between the pathologic response groups (p=0.037), which were lower in those patients who achieved CPR. The AUC for evenness was 0.844 (IC: 0.667-1.000), p=0,011. An evenness value of <0.8639 showed a sensitivity of 50% and specificity of 100% identifying patients with CPR.
Moreover, the clonal space of the TOP 1% clones in diagnostic samples was higher in patients that achieved CPR (p=0.002). The AUC of this novel biomarker was 0.9667 (IC: 0.897-1.036) (p=0.0006). A TOP 1% clonal space higher than 0.1607 showed a sensitivity of 90% and specificity of 88.9% identifying patients with CPR.
Conclusion
Our results support the association between the uneven distribution of T-lymphocytes clones proportions present in the tissue at diagnosis and response to chemoimmunotherapy. Specifically, higher clonal space occupied by the TOP 1% clones seems to outperform PD-L1 and TMB as predictive biomarker of CPR in NSCLC patients receiving neoadjuvant chemoimmunotherapy.
