AI, Immunotherapy, More Key Lung Cancer Advances Highlighted at 2025 ELCC

Together, they tackled important topics like the most impactful studies presented at the conference, the use of artificial intelligence in cancer care, and where the field may be headed.

Advances in the lung cancer spaces are always hot topics that clinicians want to discuss. A recent panel from the European Lung Cancer Congress (ELCC) 2025 discussed the use of immunotherapy benefits across treatment paradigms for patients with lung cancer.¹

The panel was led by Angela Lamarca, MD, PhD, MSc, a gastrointestinal medical oncologist at the Fundacion Jimenez Diaz University Hospital in Madrid, Spain. She was joined by Alessandra Curioni-Fontecedro, MD, head of Medical Oncology at the Cantonal Hospital of Fribourg and full professor of oncology at the University of Fribourg in Switzerland; Marina Garassino, MD, professor of medicine at the University of Chicago Medicine; and Martin Reck, MD, PhD, head of the Clinical Trial Department at the Department of Thoracic Oncology at the Lung Clinic Grosshansdorf in Germany.

Together, they tackled important topics like the most impactful studies presented at the conference, the use of artificial intelligence (AI) in cancer care, and where the field may be headed.

Hot Topics from ELCC 2025

MARIPOSA

Garassino begun the discussion by highlighting the results from the phase 3 MARIPOSA trial (NCT04487080) assessing amivantamab-vmjw (Rybrevant) plus lazertinib (Lazcluze) for patients with non–small cell lung cancer (NSCLC) harboring EGFR exon 19 deletions or L858R mutations.²

“We have already seen the results of the progression-free survival [PFS] almost a couple of years ago; they showed a benefit in terms of PFS [with amivantamab/lazertinib]. We were waiting for the update on overall survival [OS]. Also, the OS is statistically significant, and the median OS has not been reached yet [in the amivantamab/lazertinib arm],” Garassino noted.

Topline data with a median follow-up of 37.8 months included a significantly longer OS with the amivantamab combination vs osimertinib (Tagrisso; HR, 0.75; 95% CI, 0.61-0.92; P <.005). The median OS for the amivantamab/lazertinib arm had not yet been reached (95% CI, 42.9- not reached [NR]). For patients in the osimertinib monotherapy arm, the median OS was 36.7 months (95% CI, 33.4-41.0).

At 42 months, 56% of patients were alive in the amivantamab/lazertinib arm vs 44% in the osimertinib monotherapy arm.

The median intracranial PFS was 25.4 months (95% CI, 20.1-29.5) vs 22.2 months (95% CI, 18.4-26.9) between both arms, respectively (HR, 0.79; 95% CI, 0.61-1.02; P = .07). At 36 months, the intracranial PFS rates were 36% vs 18%.

Any-grade adverse effects (AEs) between the amivantamab/lazertinib and osimertinib arms included paronychia (69% vs 30%), rash (64% vs 32%), diarrhea (32% vs 47%), hypoalbuminemia (51% vs 7%), and infusion-related reactions (65% vs 0%).

“It’s important to say that the combination with amivantamab is quite toxic. There is a high degree of discontinuation of the drug. It requires very active prophylaxis with antibiotics and active help [for] the patients because they [may] develop severe skin toxicity and paronychia,” Garassino concluded.

KEYNOTE-799

Reck transitioned the topic of conversation to results from the phase 3 KEYNOTE-799 trial (NCT03631784).³ Investigators of this trial looked at pembrolizumab (Keytruda) in combination with chemoradiotherapy for patients with stage III NSCLC. Reck, who was the main presenter, noted the 2 cohorts included patients with squamous disease or nonsquamous cell histology.

“We do see consistent response rates in the 2 cohorts between 71% and 76%,” Reck noted regarding the 5-year update. “We are talking about the 4-year PFS rate, which is 39% to 46%, and we have matured 4-year OS data, between 40% and 55%. The median OS was between 36 and 57 months. These are somewhat good data for patients with stage III, unresectable NSCLC.”

Interpretation of these data should be done with caution because they are only phase 2 data, Reck commented.

SOHO-01

Curioni-Fontecedro cited the phase 1/2 SOHO-01 trial (NCT05099172) results as the most prevalent from the congress.⁴ This trial looked at BAY 2927088 for patients with EGFR/HER2-mutated NSCLC.

“There are 2 populations of patients included here: patients who received previous chemoimmunotherapy but no targeted treatment for HER2, and a second group of patients who have received [chemoimmunotherapy] as well as treatment specific for HER2,” Curioni-Fontecedro said.

In cohort D, which included those naïve to HER2-targeted therapy, the overall response rate (ORR) was 70.5%, and the disease control rate (DCR) was 81.8%. In cohort E, for those who progressed on HER2-targeted antibody-drug conjugates, the ORR was 35.3%, and the DCR was 52.9%. Between the 2 cohorts, a complete response was noted in 2.3% vs 0%, a partial response in 68.2% vs 35.3%, and stable disease in 15.9% vs 32.4%.

The most common treatment-related AE was diarrhea, although no patients discontinued due to this.

“This leads to looking at 2 main aspects. First, when should we use these targeted treatments? Should we use them earlier? The second [aspect] is that we need to test the patients. If we don’t test for these rare mutations, we will not be able to give the right treatment. We need to be precise, define the mutation, and eventually include patients in studies with these drugs,” Curioni-Fontecedro concluded.

AI Use in Lung Cancer Treatment

Lamarca then asked the panelists if any relevant data on AI were being presented during the congress. Reck highlighted the APOLLO 11 trial (NCT05550961), which evaluated efficacy with long-term immunotherapy use based on data provided from a machine learning-based analysis.⁵

The Shapley Additive Explanation (SHAP) analysis confirmed that high ECOG performance status, liver and bone metastases, PD-L1-negative status, and squamous histology were associated with higher risk. Additionally, the model predicted long-term survival at 0.78 accuracy and 0.77 area under the curve.

“They looked at a variety of patient-related data to find something like an algorithm to predict the efficacy of immunotherapy. This is our problem that we currently [have], besides the PD-L1 expression; we do not have a good predictive marker or efficacy for checkpoint inhibitors,” Reck said.

Garassino is currently leading a trial called the iFree Lung trial, which will identify patients who will benefit from immunotherapy. Garassino also commented on the APOLLO 11 trial regarding how AI parameters are not better than previous clinical parameters. She hoped there will be a dedication to all the “omics” to best identify who will benefit from immunotherapy.

Importance of Toxicity Recognition/PROs

For Reck, quality of life (QOL) parameters plus patient-reported outcomes (PROs) have become an important focus. Most trials are currently putting an “equal effect” on QOL. He believed the time to deterioration with tumor-related symptoms is a surrogate marker for disease stabilization. Data for these markers are being collected in prospective trials.

Regarding the MARIPOSA regimen, when amivantamab/lazertinib is given in the frontline setting, Curioni-Fontecedro wanted to know if everything should be given upfront with QOL considered after. She believed that while symptoms from tumor burden may decrease, AEs may increase, and this is where patient education becomes important.

“We also have to explain how these [AEs] can impair the QOL of these patients, and we can only do it through the PROs,” Curioni-Fontecedro said.

Future Directions

Looking forward, Curioni-Fontecedro hoped to see a collaborative effort to better understand resistance mechanisms regarding treatment with immunotherapy. She highlighted that it’s common knowledge that patients will likely relapse with immunotherapy.

“My hope for the future would be if we can integrate all the information related to these patients from all the different studies or academic centers, then we might be able to achieve and understand how to approach each single patient in a more specific and targeted manner by reducing the AEs and improving the response to the treatment,” Curioni-Fontecedro concluded.

Reck said he would like to see more regarding resistance to immunotherapy and how the perspective on immunotherapy has shifted. He would also like to see an evolution in the prognosis of patients with advanced lung cancer by using new advancements like T-cell engagers, bispecific antibody vaccines, or cellular therapies.

Garassino echoed Reck’s sentiments. She also believed AI is on the rise and will help with drug discovery. Additionally, she hoped options will become abundant and that experts will be discussing how to properly sequence them all.

References

1. Lung cancer: where long-term immunotherapy benefits meet treatment sustainability. ESMO virtual press briefing. March 27, 2025.
2. Yang JCH, Kim YJ, Lee SH, et al. Amivantamab plus lazertinib vs osimertinib in first-line EGFR-mutant advanced NSCLC. Presented at the European Lung Cancer Congress 2025; Paris, France; March 26-29, 2025. Abstract 4O.
3. Reck M, Lee KH, Frost N, et al. Pembrolizumab (pembro) plus concurrent chemoradiation therapy (cCRT) in unresectable locally advanced non-small cell lung cancer (NSCLC): Final analysis of KEYNOTE-799. Presented at the European Lung Cancer Congress 2025; Paris, France; March 26-29, 2025. Abstract 186O.
4. Girard N, Loong HH, Goh BC, et al. Phase I/II SOHO-01 study of BAY 2927088 in patients with previously treated HER2-mutant NSCLC: safety and efficacy results from 2 expansion cohorts. Presented at the European Lung Cancer Congress 2025; Paris, France; March 26-29, 2025. Abstract 3O.
5. Miskovic V, Mazzeo L, Silvestri C, et al. AI-based prediction of long-term survival in NSCLC patients treated with immunotherapy: Insights from the multicentric APOLLO11 study. Presented at the European Lung Cancer Congress 2025; Paris, France; March 26-29, 2025. Abstract 11MO.