Filip Bednar

Incidentally found 🫧 pancreatic cysts The numbers 🔢 don’t lie! 6️⃣ % among 21k screened have a cyst 🤏 Size is minimal! 99% are below 3 cm 🧐 So don’t we need better policies?! Looking forward to global GLs soon.. In @JAMANetworkOpen 💥 jamanetwork.com/journals/jaman…

@SyedAAhmad5 Vertical pathway inhibition has also been around a bit - KRASi + MEKi for example in this context. And colorectal cancer taught us a long time ago that hitting one part of the pathway isn’t enough - this is why EGFRi only work in KRASwt tumors.

@SyedAAhmad5 Is everyone/anyone REALLY surprised by this?The only place where solo agent targeted therapy was really effective was with Gleevec and even there it wasn’t perfect. The concept of resistance has alwys been the norm with these approaches.

Nice post highlighting that kras inhibitors are progress but not the magic bullet all of us were hoping for.

A massive March awaits. Mauricio Pochettino has selected his 27-man roster for upcoming matches against Belgium and Portugal! #NeverChaseReality | @ATT

@TheNotoriousHPB @SyedAAhmad5 @JAMAOnc @ArndtVogel Although conceptually it tries to mirror the radiation-of-mets approaches in some vague ways, which showed some efficacy in the past, so I can’t completely sink the idea. However, also not surprised here…

@SyedAAhmad5 @JAMAOnc Said on @ArndtVogel 🧵…I’m confused here. I’m not aware of anyone “debulking” colorectal mets at an 80% level akin to NET management. For colorectal liver met patients, unless I can clear 100% of the gross disease, I don’t operate. For PSM, same idea - intent is all-or-none.

Not surprised by results. 👇🏼👇🏼 Tumor Debulking in Combination With Chemotherapy in Multiorgan Metastatic Colorectal Cancer: The ORCHESTRA Randomized Clinical Trial ⁦@JAMAOnc⁩ jamanetwork.com/journals/jama/…

Everyone is talking about personalized mRNA cancer vaccines. I want to share two recent Nature papers that cut through the excitement and reveal something the viral posts aren't telling you: the approach works — but only in patients whose immune system actually responds to the vaccine. In the PDAC trial, that was half. Papers: — TNBC-MERIT trial (Nature 2026): nature.com/articles/s4158… — PDAC 3-year follow-up (Nature 2025): nature.com/articles/s4158… Here's the exact number that explains why. The PDAC trial: at 3.2 years median follow-up, vaccine responders had median recurrence-free survival that was never reached. Non-responders: 13.4 months. HR = 0.14. The T cell memory is real — some clones are projected to persist for over a decade. The TNBC trial: 10 of 14 patients remained relapse-free at 5 years. One patient has been in remission for over 6 years, with neoantigen-specific T cells still circulating at ~2% of her CD8 repertoire. So what separates responders from non-responders? Across both trials: only 41 of 251 neoantigens actually triggered a T cell response. That's 16%. Each vaccine encodes up to 20 neoantigens — the algorithm's best guess at which tumor mutations will be immunogenic. Most don't work. Half the PDAC patients didn't respond — not because they couldn't mount an immune response (they responded fine to concurrent COVID vaccines) — but because their selected neoantigens happened to miss. This is the core unsolved problem: predicting, from sequence alone, which mutations will produce peptides that a specific patient's immune system will actually recognize. It sounds like an MHC binding problem. It isn't. Tools like NetMHCpan handle binding affinity reasonably well. What they miss is the full causal chain: 1. Proteasomal processing — will the protein actually be cleaved into this exact peptide? 2. TAP transport — will it reach the ER for MHC loading? 3. HLA-peptide stability — across the patient's specific HLA alleles (10,000+ variants in the population) 4. T cell repertoire availability — has central tolerance already deleted the clones that would recognize it? 5. Tumor clonal architecture — is this mutation in every tumor cell, or just 30%? Targeting subclonal neoantigens leaves most of the tumor untouched. Every step is a filter. Current prediction stops at step one. Compounding everything: average manufacturing time in the TNBC trial was 69 days (range: 34–125) from sample to vaccine release. For pancreatic cancer, where non-responders recur at 13.4 months post-surgery, that's not a footnote. It's a window closing. The good news: the T cell biology is sound. The mRNA platform works. The immunology is spectacular — when it works. The bottleneck is the first step: choosing which 20 neoantigens go in the vaccine. Get that prediction right, and the responder rate moves. This is where AI in cancer immunotherapy has to go next. Not mRNA design. Not LNP formulation. Immunogenicity prediction — integrating mutation calling, HLA typing, T cell repertoire sequencing, and single-cell tumor expression simultaneously, as a causal inference problem, not a binding affinity lookup. We don't have a model that does this well. That's the gap.

@PracheeAC Someone very smart once called this “stamp collecting”…

At least for now, every aspect of biology we study suspends consideration of many layers of complexity we know exist (and many more we don’t). What about microenvironment, or gene regulation/epigenetics, or viscosity, or quantum effects? We’ve undoubtedly learned some very interesting things. The problem is that this often drives massive efforts to measure and model particular dimensions of complexity as if they contain the decisive signal. We brute-force the next untapped layer, as if greater descriptive richness will necessarily or reliably give rise to causal understanding. A pernicious threat here is that cost (given the high cost of next-generation, complexity-tapping technologies) and sheer volume of data (when all data are not of equal value) become proxies for greater insight. Not to glorify things for which we had lower resolution and signal outlasted the noise, but in some ways I think our scientific predecessors had a lot of creativity with far less firepower than what we can currently deploy. They were forced to design truly elegant experiments and better identify where missing complexity had outsized value. As we continue to grapple with the step change afforded by our new capabilities, it seems just as important to recover that kind of judgment in deciding where and how frontier technologies are best deployed.

@kevinmd @juliomayol Yes

"We are not ‘burned out.’ We have been gaslit." 🛑 After 15 years of training and $300,000+ in debt, Dr. Corina Fratila just published a blistering, unfiltered essay about why she is ready to drop her stethoscope faster than Big Pharma drops accountability. She argues that doctors are no longer allowed to be healers. They have been forced into becoming "glorified data-entry monkeys in a Kafkaesque insurance labyrinth," spending their days begging insurance companies for permission to save lives and timing their own bathroom breaks. Her shockingly honest comparison of modern medicine to a vastly different (and highly controversial) profession is breaking the internet today. It is raw, it is darkly hilarious, and it is a heartbreaking look at what is really happening behind the clinic doors. "Every day feels like a hostage negotiation between your soul and your malpractice insurance. The system isn't broken. It is working exactly as designed. For profit. Not for people." Healthcare workers and patients: Is Dr. Fratila right? Drop a 💯 in the comments if you feel this, or tag someone who needs to see the truth. 🗣️ Link to the full article in the comments below! 👇

The NIH cancer curve just broke. As of Mar 03, NIH cancer funding is ⇣1,308 awards behind what the 5-year median should be. That’s a 57% shortfall. @Nature lit the match on this story so we dug deeper to lift the curtain specifically for cancer. If this trend holds, the effects are both immediate & long term. So many questions remain unanswered. This week we’re breaking it all down: • Which mechanisms are most delayed (R01 vs U vs P) • Which cancer areas are absorbing the hit • Which institutions are most exposed • Where it hits first: screening, trials, imaging, prevention, survivorship If you run a lab, grants office, or cancer center, tell us what cut you want. I'll send you a report for free + maybe also publish it for on here. Source: NIH RePORTER via @Jori_health

In a new study, U-M researchers have developed a mouse model that mirrors liposarcoma in humans. Learn from Dr. Angeles @cvangelesMD how the new mouse model can help researchers develop novel therapies: michmed.org/Q9VJA.

I think that writing deep, important, and enjoyable things demands a sort of Prestige Death. When I worked as a scientist, the most prestigious thing to do was publish in Cell, Nature, or Science. But I didn’t enjoy this. It forced me to always think about what other labs were doing, or what particular editors wanted to see. It made me think about how I could tell an artificial “story,” rather than just do the experiments that seemed most interesting to me. Then, I became a science journalist. I was taught that writing for, say, Scientific American was the pinnacle of prestige. (Haha.) But then I did that, and realized that I didn’t enjoy it at all. The editors skimmed off all the technical details, to the point where my explanations became shallow and weak. Mechanistic details about the biology were cut out. The goal, instead, was to write a piece for mass consumption; something anybody could understand. But this is generally not a good thing if you're deeply serious about using writing as a vehicle to understand something! So I started a blog, and began publishing 90% or more of all my writing there. A blog is probably the least prestigious thing you can do as a writer. My journalist friends thought it was foolish, because blogs do not pay bills. But I’m convinced it was basically the *only* way that I could be fully, unapologetically true to my own writing style and interests. When you write your own things — without consideration for editors or “mass appeal” or “prestige” — I think you will be more creative. Your writing will be deeper, more comprehensive, and more enjoyable! In other words, I think that to do your best work, it's sometimes helpful to separate what you do for prestige vs. what you do for yourself.

I got mine! Time to get yours! Great job Polly. Thank you for this. @NoStomach4Cancr #CDH1

We need to work with our medical oncology and general surgery colleagues to share the importance of laparoscopic staging more broadly. I have seen too many unnecessary EUS procedures are done yet no laparoscopy is performed for advanced T stage lesions. @ASCO @AmCollSurgeons

@SyedAAhmad5 @umichbball @DukeMBB You get this round! April rematch!

@Fil_Bednar @umichbball @DukeMBB Great game. See you in April.

Tight game so far, @SyedAAhmad5! Let’s see who goes the distance! Go Blue! @umichbball @DukeMBB

@Alex_Kim_HIPEC @SocSurgOnc @acpmpresearch @UTSW_Surgery @utswcancer @UTSWMedCenter Well deserved! Keep it going!

@SocSurgOnc @acpmpresearch So appreciative and honored to be the recipient, thank you SSO!! @UTSW_Surgery @utswcancer @UTSWMedCenter

Congratulations to the 2026 Clinical Investigator Award recipients! Through this highly competitive program, SSO and @acpmpresearch are proud to invest in groundbreaking clinical research that moves surgical oncology forward and strengthens the science behind patient care.

The future is bright for pancreas cancer research! Today, trainees from the Rogel and Blondy Center for Pancreatic Cancer gathered to discuss exciting science during their monthly journal club. Great discussion! Great collaboration! @UMRogelCancer @LyssiotisLab @Pasca_Lab @Fil_Bednar @timofran1

Another great study looking at physician burnout by @UCSFSurgery as led by @CLebares Medical student Yash Shroff did a superb job presenting @PCSAsurg . Leadership at your institution and the culture they represent is a strong predictor of burnout. Amenities don’t really matter as much to make up for the leadership. #PCSA2026

Outstanding job! Take note @TempleHealth @FoxChaseCancer ! Representing Owls well!

Round 2 @PoojaParikh28 presenting at #ASC2026 on #socialvulnerability in PDAC! ➕Vinay Kumar 3rd year med 👨‍🎓 @templemed speaking about our 🧨 data on distal PDAC 🔥 Great session by @benfergvson and @Fil_Bednar @UMichSurgery @FoxChaseCancer @TempleHealth @UnivSurg @AcademicSurgery