SEOM

Somos una sociedad científica, referente en cáncer. Nuestra misión: mejorar la prevención, el diagnóstico, el tratamiento y el seguimiento del cáncer.

[SEOM @_SEOM]

💻 Disponible la #RevistaSEOM digital de agosto.
✅️ Guía imprescindible para vivir #SEOM26, el Congreso del 50 aniversario.
✅️ CTO refuerza su liderazgo aumentando su factor de impacto.
✅️ Registro TESEO, un caso de éxito.
✅️ Jornada SEOM de Tutores MIR 2026.
✅️ Nuevo reportaje de la serie sobre la historia de la Oncología Médica (década 1996-2006) con motivo de #50AñosSEOM.

🔗 https://t.co/ucBgNIcN0b

[SEOM @_SEOM]

@MarioBalsaMD @hospitalclinic @OncoAlert ¡Feliz cumpleaños @MarioBalsaMD! 🎂🎂🎂

[Enrique Grande @drenriquegrande]

🧬 HOW DOES A PERSONALIZED mRNA CANCER VACCINE ACTUALLY WORK?

As an oncologist, and also as a university professor, I strongly believe that understanding how a new treatment works is often the best way to understand why it may eventually change our clinical practice.

So, what exactly is a personalized mRNA cancer vaccine?

The concept is both sophisticated and surprisingly intuitive.

1️⃣ Start with the patient's own tumor 🧬

Every cancer is genetically different.

By sequencing tumor DNA and RNA, and comparing this information with normal tissue , we can identify tumor-specific mutations.

Some of these mutations generate abnormal proteins that are not present in healthy cells.

These are called neoantigens.

And importantly, they can become molecular "flags" allowing the immune system to distinguish cancer cells from normal cells.

2️⃣ Select the best targets 🎯

Not every mutation will generate an effective immune response.

Bioinformatic algorithms therefore analyze the patient's tumor and predict which neoantigens are most likely to be recognized by their immune system.

In the case of intismeran autogene, up to 34 patient-specific neoantigens can be selected.

3️⃣ Build an individualized mRNA therapy 💉

Here comes the fascinating part.

A synthetic mRNA sequence encoding those selected neoantigens is manufactured specifically for that individual patient.

Think about what this means.

We are no longer simply choosing the best available drug for a patient.

We are manufacturing a treatment based on the molecular identity of that patient's own cancer.

4️⃣ Teach the immune system what to recognize 🛡️

After administration, the mRNA enters cells and provides the instructions to produce the selected neoantigens.

These neoantigens are processed and presented to the immune system, activating tumor-specific CD4+ and CD8+ T cells.

The objective is to generate an immune response capable of recognizing cells carrying those same neoantigens.

5️⃣ Let T cells search for the cancer 🔎

Those activated T cells can then recognize tumor cells displaying the corresponding antigens and potentially destroy them.

This is why combining personalized vaccination with PD-1 blockade such as pembrolizumab makes so much biological sense:

🎯 The vaccine may teach the immune system WHAT to attack.

🔓 Checkpoint inhibition may help the immune system KEEP attacking it.

And this is where, in my view, the concept becomes much bigger than one drug or one tumor type.

For many years, we have defined precision oncology as:

“the right treatment for the right patient.”

Personalized mRNA vaccines introduce an even more ambitious paradigm:

“a treatment designed and manufactured specifically from the molecular characteristics of one patient's cancer.”

@OncoAlert @_SEOM @moderna_tx @GEPAC_

Figure adapted from: doi:10.3390/cancers17091408.

[Mario Balsa @MarioBalsaMD]

This is cell therapy engineering at its best 🧬🔥

Genome-wide CRISPR screening in vivo identifies two complementary brakes on T-cell performance in solid tumors:
▪️P2RY8–Gα13: limits tumor infiltration
▪️GNAS–Gαs: drives T-cell dysfunction
▪️Dual knockout; further improves tumor control across CAR-T & TCR models

The exciting part? We are moving from asking which T cells work to systematically engineering why they should work better inside the tumor 💥

@OncoAlert
@oncodaily @_SEOM @myESMO

[Mario Balsa @MarioBalsaMD]

🚨 Circulating B- & T-cell activation states predict outcomes in #melanoma under checkpoint inhibition @jitcancer
https://t.co/mMnfq1gojJ

▪️High-dimensional peripheral immune profiling
⚠️ Pre-Tx ↑PD-1+ T cells → irAEs
🔴 Naïve/DN B-cell states → poorer outcomes
💥 On-Tx class-switched B cells + activated T cells → improved survival

B cells clearly have a say in how the plot unfolds!

@OncoAlert
@OncoReporte @myESMO @_SEOM

[Vilma P. Barcia MD, PhD, MSc @DrVilmaPBarcia]

🌟 A milestone for #PANTHEIASEOM! Proud to share our study in Pancreatology, congratulations @kimtruss @aminoaxid and co-authors.
📊 672 pts: ⬆️ #SIRI predicted poorer survival & response, greater liver tumor burden & #cachexia in metastatic #pancreaticcancer.
@_SEOM @OncoAlert

[Nieves Martinez Lago MD PhD @DraMartinezLago]

💙 Very proud of the PANTHEIA-SEOM team!

🧬 Metastatic PDAC | 672 pts, 30 centers

🔥 SIRI >2.3
📉 mOS 9.2 vs 14.0 mo
⏳ mPFS 3.9 vs 5.9 mo
🎯 ORR 25% vs 37%

💡 SIRI independently identifies a poorer-prognosis, lower-response phenotype.

🔗 https://t.co/5a6yb1kaPR

@OncoAlert

[Mario Balsa @MarioBalsaMD]

💊 The evolving landscape of CDK inhibitors in cancer therapy and beyond! @NatRevDrugDisc
https://t.co/Y3nHTH7sgo

▪️ CDK4/6i transformed breast cancer, but resistance remains key
🧬 CDK2 inhibition may tackle refractory disease
🎯 HER2/PI3K combinations + next-gen selective CDK4 inhibitors broaden the horizon

After a decade of CDK4/6, the cell cycle is far from coming full circle 🔄

@OncoAlert
@OncoReporte @myESMO @_SEOM

[Mario Balsa @MarioBalsaMD]

🧬 TAK1: a tumor-intrinsic cytokine toxicity checkpoint controlling anti-cancer immunity (CRISPR screens, preclinical) @CellReports
https://t.co/cX7AaR0n4X

▪️ TAK1 protects tumor cells from TNF + IFNγ-mediated killing
💥 TAK1 loss → cFLIP degradation → RIPK1/caspase-8 apoptosis
🎯 TAK1 loss improved tumor control & enhanced adoptive T-cell therapy in vivo

A way to help T cells take the tumor down could be…to take TAK1 away 😉

@OncoAlert
@OncoReporte @myESMO @_SEOM

[Mario Balsa @MarioBalsaMD]

🧬 Why are early-onset cancers rising? A timely @CellPressNews perspective on accelerating cancer-cause discovery
https://t.co/zZuiCvNDy5

💥 Rising incidence reported across 42 countries, with strong birth-cohort effects
🎯 Tighter integration of epidemiology + mechanistic biology
▪️ Proposes 3 frameworks: tissue ecosystems, dynamic biological risk & cancer preventability

So…are we looking for the causes of early-onset cancer with the right lens or are we still asking new questions with old epidemiology?

@OncoAlert
@OncoReporte @myESMO @_SEOM

[Mario Balsa @MarioBalsaMD]

🚨 Can circulating TKa guide treatment sequencing in BRAFm M1 melanoma? (SECOMBIT, n=81)
https://t.co/13ipb9XvVo

🎯 5y total PFS: 60.8% TKa-low vs 35.0% TKa-high (P=0.004)
💥 5y OS: 70.7% vs 36.9% (P<0.001)
▪️TKa-high patients showed better outcomes with the “sandwich” strategy
📈 TKa increased at PD: potential dynamic disease marker

SECOMBIT could be moving from sequencing by strategy to sequencing by biology…with TKa deciding who really needs the sandwich 🥪

Congrats @AnaArance1 @PAscierto and all the team! 👏🏼

@OncoAlert
@OncoReporte @myESMO @_SEOM
@GrupoMelanoma

[Mario Balsa @MarioBalsaMD]

🚨 The next generation of antibody–drug conjugates (Perspective: @FerMosele @jsoriamd @FAndreMD)
https://t.co/lRvwG68y5N

🎯 Multi-dimensional biomarkers may enable personalized ADC selection
⚡ Diversified constructs & optimized drug-to-antibody ratios could improve efficacy
👀 Faster development frameworks are needed to match the pace of ADC innovation

The next generation of ADCs should carry better ideas 🤔

@OncoAlert
@OncoReporte @myESMO @_SEOM

[SEOM @_SEOM]

🏃‍♂️ El reto solidario de Nicolás de las Heras, dentro de @BiciRacing #RoberContraElCáncer, ha llegado a @A3Noticias.

Los fondos recaudados durante el #CaminoDosFaros se destinarán al Programa de Becas, Proyectos y Premios de SEOM, impulsando la investigación y la formación en Oncología Médica para seguir mejorando la atención a las personas con cáncer.

💚 ¡Gracias, Nico, por convertir cada kilómetro en apoyo a la investigación!

[Mario Balsa @MarioBalsaMD]

🧬 Germline variants in cancer susceptibility genes among patients with mucosal melanoma (n=346; 322-gene panel)
https://t.co/gXZBtsZJUQ

🎯 Germline pathogenic variants in 10.7% (37/346)
▪️ CHEK2, ATM & MITF were most frequent
💥 MITF p.E318K (OR 6.0) and CHEK2 c.1100delC (OR 6.7) enriched vs population controls
👪 ≥2 affected first-degree relatives: 49.0% vs 29.1% (P=0.019)

@OncoAlert
@OncoReporte @myESMO @_SEOM
@GrupoMelanoma

[Mario Balsa @MarioBalsaMD]

🚨 Clinical toxicity of ADCs and ICI–ADC combinations! @NatRevClinOncol
https://t.co/pcOM3r9Bho

▪️ Unified framework separating immune-, payload- and target-related toxicities
🫁 Recognize organ-specific toxicity patterns and manage overlapping ICI–ADC toxicities as immune-mediated until proven otherwise
💥 Practical algorithms for treatment interruption and rechallenge!

The real payload isn’t just the drug, it’s knowing who carries the toxicity 🎯

Congrats to @peters_solange @PGrivasMDPhD @stolaney1 and all the team! 👏🏼 amazing!

@OncoAlert
@OncoReporte @myESMO @_SEOM
@Lung_Cancers @LungCancerRx

[Oriol Mirallas MD @DrMirallas]

🥳 Out in the August issue of @Annals_Oncology

👏🏻 Thanks to all the authors who made it possible
@PaulJiL @Paul_TdL @GiuliaPretelli @ahernandocalvo @MarioBalsaMD @champiatMD

@_SEOM @myESMO @ASCO @OncoAlert

📖 Open Access:
https://t.co/LYpahdWwtw

[Mario Balsa @MarioBalsaMD]

🧬 Immunologic determinants of response to TIL therapy in advanced melanoma! @CellPressNews
https://t.co/KFnPJMja49

🎯 Durable ORR 36% | CR 14% | mPFS 8 mo
▪️ Response linked to CD8+ stem-like & LAG-3+ tumor-reactive TILs
▪️ Tertiary lymphoid structures → ↑ response & PFS
⚠️ Prior ICI exposure → ↓ TIL fitness

@OncoAlert
@OncoReporte @myESMO @_SEOM
@GrupoMelanoma

[Mario Balsa @MarioBalsaMD]

🩸 Longitudinal BRAF ctDNA monitoring after melanoma resection (prospective real-world cohort, n=127; 318 samples)
https://t.co/qxHrNLuhWV

🎯 ctDNA detection tracked disease status: OR 5.90 locoregional | 7.21 metastatic vs NED (both P<0.001)
💥 Detectable ctDNA → HR 17.17 for relapse (P<0.001)
📈 Each ctDNA doubling → HR 1.53 (P<0.001)
⚠️ Strong prognostic signal, but limited sensitivity

The future of melanoma surveillance is not only about what we can see, but what we can already detect🩸

Congrats to @susana_puig and all the authors! 👏🏼

@OncoAlert
@OncoReporte @myESMO @_SEOM @GrupoMelanoma

[El Médico Interactivo @Elmedicoint]

La inmunoterapia se consolida en el tratamiento del cáncer de cabeza y cuello: @_SEOM actualiza los avances terapéuticos con motivo del Día Mundial, que se celebra cada 27 de julio
#DíaMundialDelCáncerDeCabezaYCuello 
#diainternacionaldelcancerdecabezaycuello 
https://t.co/Ol3NkdtEq8

[Mario Balsa @MarioBalsaMD]

🧬 POLR1A: a new driver of melanoma metastasis? (in vivo CRISPR screen, preclinical)
https://t.co/AKGaXN76cw

🔴 High POLR1A expression → worse OS (HR 1.99)
🫁 POLR1A loss impaired migration, invasion & lung colonization
💥 Pol I inhibition with CX-5461 reduced tumor growth and lung metastases

Pol I may be transcribing more than rRNA… 📝

@OncoAlert
@OncoReporte @myESMO @_SEOM @GrupoMelanoma